From 67e1da8f6ad6e464c6f55704c7bc62eb12fc4c9a Mon Sep 17 00:00:00 2001 From: jkool702 Date: Thu, 21 May 2026 16:03:41 -0400 Subject: [PATCH 01/10] initial test - superscalar prefetch engine --- UNIT_TESTS/c_plugin_test/forkrun_plugin.h | 36 + UNIT_TESTS/c_plugin_test/plugin_ctx_math.c | 9 + UNIT_TESTS/c_plugin_test/plugin_ctx_math.so | Bin 0 -> 11840 bytes UNIT_TESTS/c_plugin_test/plugin_echo.c | 5 + UNIT_TESTS/c_plugin_test/plugin_echo.so | Bin 0 -> 11640 bytes UNIT_TESTS/c_plugin_test/plugin_poison.c | 16 + UNIT_TESTS/c_plugin_test/plugin_poison.so | Bin 0 -> 11760 bytes UNIT_TESTS/c_plugin_test/test_basic.c | 9 + UNIT_TESTS/c_plugin_test/test_basic.so | Bin 0 -> 11760 bytes UNIT_TESTS/c_plugin_test/test_ctx_header.c | 13 + UNIT_TESTS/c_plugin_test/test_ctx_header.so | Bin 0 -> 11840 bytes UNIT_TESTS/c_plugin_test/test_ctx_naked.c | 28 + UNIT_TESTS/c_plugin_test/test_ctx_naked.so | Bin 0 -> 11840 bytes forkrun_ring.c | 647 +++---- forkrun_ring.native.so | Bin 0 -> 141896 bytes forkrun_ring.x86-64-v2.so | Bin 0 -> 137800 bytes forkrun_ring.x86-64-v3.so | Bin 0 -> 145992 bytes forkrun_ring.x86-64-v4.so | Bin 0 -> 145992 bytes frun.new.bash | 1746 +++++++++++++++++++ 19 files changed, 2214 insertions(+), 295 deletions(-) create mode 100755 UNIT_TESTS/c_plugin_test/forkrun_plugin.h create mode 100644 UNIT_TESTS/c_plugin_test/plugin_ctx_math.c create mode 100755 UNIT_TESTS/c_plugin_test/plugin_ctx_math.so create mode 100644 UNIT_TESTS/c_plugin_test/plugin_echo.c create mode 100755 UNIT_TESTS/c_plugin_test/plugin_echo.so create mode 100644 UNIT_TESTS/c_plugin_test/plugin_poison.c create mode 100755 UNIT_TESTS/c_plugin_test/plugin_poison.so create mode 100644 UNIT_TESTS/c_plugin_test/test_basic.c create mode 100755 UNIT_TESTS/c_plugin_test/test_basic.so create mode 100644 UNIT_TESTS/c_plugin_test/test_ctx_header.c create mode 100755 UNIT_TESTS/c_plugin_test/test_ctx_header.so create mode 100644 UNIT_TESTS/c_plugin_test/test_ctx_naked.c create mode 100755 UNIT_TESTS/c_plugin_test/test_ctx_naked.so create mode 100755 forkrun_ring.native.so create mode 100755 forkrun_ring.x86-64-v2.so create mode 100755 forkrun_ring.x86-64-v3.so create mode 100755 forkrun_ring.x86-64-v4.so create mode 100755 frun.new.bash diff --git a/UNIT_TESTS/c_plugin_test/forkrun_plugin.h b/UNIT_TESTS/c_plugin_test/forkrun_plugin.h new file mode 100755 index 00000000..59459faf --- /dev/null +++ b/UNIT_TESTS/c_plugin_test/forkrun_plugin.h @@ -0,0 +1,36 @@ +// forkrun_plugin.h +#ifndef FORKRUN_PLUGIN_H +#define FORKRUN_PLUGIN_H + +#include + +// Opt-in flag: define this in exactly ONE of your C files to receive the context +// int forkrun_use_ctx = 1; + +struct forkrun_ctx { + uint64_t batch_index; // global batch sequence number + uint64_t batch_offset; // byte offset in input stream + uint64_t batch_byte_length; // length of current batch in bytes + uint32_t version; // struct version, currently 1 + uint32_t worker_id; // internal worker ID + uint32_t node_id; // NUMA node ID + uint32_t num_kills; // retry count for this batch (if failure recovery active) + uint32_t numa_major; // NUMA major sequence (0 if not NUMA) + uint32_t numa_minor; // NUMA minor sequence (0 if not NUMA) + int32_t fd_in; // input memfd file descriptor + char delimiter; // batch delimiter character + uint8_t cfg_state[3]; // global configuration state +}; + + +/* === FUNCTION DEFINITION TEMPLATES === + * + * 1. Standard Fast Path (2-arg): + * int my_func(int argc, char **argv) { ... } + * + * 2. Context-Aware Path (3-arg): + * int forkrun_use_ctx = 1; + * int my_func(int argc, char **argv, const struct forkrun_ctx *ctx) { ... } + */ + +#endif // FORKRUN_PLUGIN_H diff --git a/UNIT_TESTS/c_plugin_test/plugin_ctx_math.c b/UNIT_TESTS/c_plugin_test/plugin_ctx_math.c new file mode 100644 index 00000000..d4a7809e --- /dev/null +++ b/UNIT_TESTS/c_plugin_test/plugin_ctx_math.c @@ -0,0 +1,9 @@ +#include +#include "forkrun_plugin.h" +int forkrun_use_ctx = 1; + +int plugin_ctx_math(int argc, char **argv, void *ctx_ptr) { + struct forkrun_ctx *ctx = (struct forkrun_ctx *)ctx_ptr; + printf("%lu\n", ctx->batch_byte_length); + return 0; +} diff --git a/UNIT_TESTS/c_plugin_test/plugin_ctx_math.so b/UNIT_TESTS/c_plugin_test/plugin_ctx_math.so new file mode 100755 index 0000000000000000000000000000000000000000..70b6006655a6f56da1748eef77f9a0781f8cd1ee GIT binary patch literal 11840 zcmeHNZ)hCX5q~G!&Bb=4bE?Lw-PqSeF0xy1CAm&rCvNm#=O8<-EQcg*vt8*{x@+!_ z*xQRG(Na^BlBA?jLI|{_&@TZK0yWL2elT2cF>ay7A+$7*fG7lHQW}-gqNL#K%zN`Y z?X6bElv4U(-*G!{{=J!?&{ZI5xiC#_Yh2dw! z9w7Yu8tHLdZgt>tjf=gFu0u-V1&BSxcH8O8mv{8!8TIWaULQ+eT3!C>==T@TZ2tOp zf4l9C%YSd%^Ks_e9)od0$5vZ^0GN~HR}2k6+gw~uCw=h*%0 zOLZFidKqVP*RK(pdHz@r5i-wjIl$m6tNy2G+24P`EPH!>scr8$R=zBdE7mCT!eeK7Op>ZVNMO6IK_emgDjGg%;6Uz%>)JG7?HzMnhxD`Kna=g(x$A6wvQ z=GpiC?X>id4k)$!7`e5arNfmiFA_8HO|spv&-&NT5)=ODICv>iey3Hbp4#$OV)oQb zG?Z$@N=Jv!Bpz`D;t0eMh$9e3AdWyBfj9zj1mXz95r~ce>SEN@eV;aRToc~L-+_fE zww*u8)5yW~U^;^15=~0cCNA4aH&G12RZw4}?zT&&y#EHQ|x#UhblLgoCqB-`|oMTVt zOHLub;Hud|btYf3r~Em)==eD`>*Y)Sw3;q^PkPmoU9GsxQ-%EGlvOEP_o>mb;{$_s zuhnZECO;FZg}ykN(_{QQG)0|V-Ic#xk=zdqyV37JzhF_$bCrr#9-yBRxhqR*6T+IF0It--y+C^dks7i3*#y=mrCs3ep_;p7V9J$ z>s=%r?NV!Mq_yLrwryvV=hTC{?muv-Q*S%gAENIZt*Q6YP;2VZRz#T?@rWZ3M<9+s z9Dz6jaRlNB#1V)i@P8Zu)C=MI0Qoi79z3=ipk9{b{SLuvQWQv;*r-Q#3m=*BF2PZk zaIVb*{D0i2mo-5O9n=ELf^%KMqf2mI91#AJrYf~fV241|D$7!jpytrIJ;|UBKq0$R z^d6NW74(Zc3sh{$kU&4`g{;aDi<`qApDO6ho7?C{|w;&?y$it z5~x24WdBD82al$^sQTKU?m0}gYEQbiyZ65Cp58<0u5mY;&N#j>4t{w*$#bmqWg_L# z{?5c9r$;TxdVo@A)dM6w<@>FLI5;=(+k~D9ZKQjI-ng$tf$QOf>QL=+BVd1WO`D)j3GPo3 zS5MM}?czBB`dKZ%qjA53{t8W^{J*dP{g-;3lsfWBtgr^7)~OM@g}MRQ2avu(lZ2v0 zq`v|B+nV04!u$PQEzqX$UIgSn)bcx32Obo{_?M>NrSLp~{0<6W3w^M6LElOAG>`y1 zMD(aW*odaD?^8WO^r*hpG|{8huWmqpf#|#^){QC8pQNT&>9kc=YyB_VFWOVw0jp4> zEL*l`3gtg7QP$SKnQskyv%CeKTJu=>ZV%Q!&ImCTCHp3oN%685vWw~89^w`P%6UPUM zO3y5NI3o&~p>ZNnXAi2QV-FAXkJ%58jGP{xuqXNl#)fG@cIKw-K-1Oh3-<0p{;uoz zMKv35p`qAhLs^yiqVG%+^gRP}n3c-DYt59Z)?_tb$R5mRm8DO^^4&RKSvp3VpK~fX zWo73}w3dOsr!?m&*Q?~qr6$BCp63=ER*>0jf!6cNS;u#j)i68jm1kYgpI4TflPjCc zk}@#kj=99f9n5(lwn1xZf1F}|ihL-O6*^ejoG~_8sVIxKU6FQ^@lv0x<@mmrpRD?{ zRsRcv^Oj(ba-;XVV2XQ@!NHFoy4Cc%WlYC&0T6i+^LT{ypC(#R|Dyb^0EQk*jlQt{ zy(Qf*h4hz1AMicm2M6>(J4%zFeLQCYk@rD9?0+9I{z4%h|l z&otp$3Hr!;@SbZ;E)?_tv9CWM-JpH^FLZUUv5+>PafCkL3UPw^$d{HyzpJ5XCeQ=? zD5Q`7^HOOeAHLpUoD*kW3+InKw|xVB35Qvnj+=?VG~6d(KtGgTYFU=SI(N_n_a@Uj zPVtfcGfHcq(hxN0y5~Q$vG+wpgWP8g_KYz3KHwS_al`YE>r$M%(J;rAdkuUoWIu#b St{JWWlYK`2-jG5FRsRO>i<*f5 literal 0 HcmV?d00001 diff --git a/UNIT_TESTS/c_plugin_test/plugin_echo.c b/UNIT_TESTS/c_plugin_test/plugin_echo.c new file mode 100644 index 00000000..c22cca4a --- /dev/null +++ b/UNIT_TESTS/c_plugin_test/plugin_echo.c @@ -0,0 +1,5 @@ +#include +int plugin_echo(int argc, char **argv) { + for (int i = 0; i < argc; i++) printf("%s\n", argv[i]); + return 0; +} diff --git a/UNIT_TESTS/c_plugin_test/plugin_echo.so b/UNIT_TESTS/c_plugin_test/plugin_echo.so new file mode 100755 index 0000000000000000000000000000000000000000..8dabd41900aac93303fdfc32f614584468a44144 GIT binary patch literal 11640 zcmeHNYit}>6~1dHblaxuZIggWO1%UJoKjD1hmDQa<=;z9oIg^#)RFCm})U}mmutzWV`r7Mjp2s zaY-&37&l_=Bl}sB@xs_CdO&?m#AD>+s}C53F!mU>0%E?C@A#R2$L@sKeOu-W^LqTwc&P+%X}N%hor;{h&9FYZli;5@942p>iOqxrr#Qx{`JA{{^$qYZ=C+g z)tCR+|9;y;|Fjq0i`y@4?xx#opI`D@YAg1_Z{y3Vwr@YNYP%28xvit0dQ8u-`&U+L z)OPnV&C^|3A<|wvw1*h>;^tipPu%dg)3CpP#0-0PZMCgqo{g6UN&hAb7x(>*Vb3l5 zg=_YuzdmVSy3uOKF57S1^0(0dugC!L+UitW$I!Yx`#yi@H4>}p=TF%Sht6@=e&HQ| z3l069hm~4;n%r8;(CPB#MH0qN)7+5XB|5{f_PYu`M0%1+l#+KZ2nFYj|)E=)~X zZ5_|E+sc0FfW5FBU;Fzly4EM&tzP9Y^)5YgdfE8ZyR@w8@zfF2X3;5%Koo%}0#O8_ z2t*NxA`nF&ia->B|HBBNE=FBVA?WAI6*b{6Kli~~cM1#FgQ+G8F7c!kZIJRjsRoWA zxJqiqA0hrOqtb9bMbrc2=MQC{U=UKrna&prPQ`c2zT+t8$iz`6{}SI0{!}< zhQarZV~n;E;A04uy&2$RFM#>00e-{2P7h0!x{D4e?KK?_@Pqn1W{M8xah*?bSYjT0 zqc}Ctv7N04cyEHo?z&d1Jxf3@4J`Y8gtjFSLF+k#ZC5gNfuo zB0jo&nUtayMIeem6oDuLQ3Rq0L=lK05JljBBm$@}!u165a;{alZ84y}C&~VOLjOgI zh))WQ`emoks8@CfjXDPZJ3{`!ty)p5B#k0!hZUi@j^WlN^gV`D-w?c4uw4+f&6?CN zs8MuHKsu-&xPIaG2?MH2id69D?>7SYc~SJJXwwbz(cf*_|1+Xb|JZ37ailUs(_eR!cT@4&@SQEpJy@P`Z=aPu9ETq zU|n(z98>ozJeQ)bzD^yU7vB%ypVj)w`g<1Ozf7HG{{MIb{?GL|ZED+AjIfT)#`zVA zTWI$HYXI86p-zl^Rux|7Z)$~v!ut@=e^={oug3@ce+VDnBjDdh0c@cU z)-Cv3iJt-yz(ksbX zg|-g^j(_Cs!iMpbRhi5C?j)gKHaLS`q3C$^O*RW52j+gpMG8eb6IR-{;124MaWzv#|a7ko~Ljn*c=K0ek%$Nd)iXP{qXwvS;+pP{MZ3YFcgIUV82EkzDG!BP)Fc>!mvJQ;3cxM_j&s*w^z3ydP@J>Sx%2@n`CAjRJe*9eBTVNfs>ZfOwAICfnfr z`2Xhh4l_f_K>ZAR;2KGS_Q+S(#J;O;X*#e2UMDv9;Xm@kWU5i$P-ZUl89$_h=f^r_ z9yi#B(lf2gatVv##23#7^V?7GS*iY%29<)MA@#E+T@5V8+70s0eA-a>J>WW&Yd>5! mzJIu$!?ha=b6)w3LH=(k*g~Y@$Gw^Tncc=}d&nR}s(%5E;*Dnj literal 0 HcmV?d00001 diff --git a/UNIT_TESTS/c_plugin_test/plugin_poison.c b/UNIT_TESTS/c_plugin_test/plugin_poison.c new file mode 100644 index 00000000..8587dc87 --- /dev/null +++ b/UNIT_TESTS/c_plugin_test/plugin_poison.c @@ -0,0 +1,16 @@ +#include +#include "forkrun_plugin.h" +int forkrun_use_ctx = 1; + +int plugin_poison(int argc, char **argv, void *ctx_ptr) { + struct forkrun_ctx *ctx = (struct forkrun_ctx *)ctx_ptr; + + // Simulate a segfault/crash on batch index 7, ONLY on the first attempt + if (ctx->batch_index == 7 && ctx->num_kills == 0) { + return 1; // Trigger failure! + } + + // On retry (num_kills > 0) or normal batches, process normally + for (int i = 0; i < argc; i++) printf("%s\n", argv[i]); + return 0; +} diff --git a/UNIT_TESTS/c_plugin_test/plugin_poison.so b/UNIT_TESTS/c_plugin_test/plugin_poison.so new file mode 100755 index 0000000000000000000000000000000000000000..87b6180e2fc7b84295e32e747f0737ba7f979d1e GIT binary patch literal 11760 zcmeHNU2Ggz6~4QU$)*kKZIcv}w9Qf+qEtnyka&p1LxrjqiM${c9*`qfQC~nQ4+tS1EKns!{M1znq*ayWoIB@R z&yLqo1rkDH?rP@T^MB^d-PwE2?6(I;hT^f9!e~-oS8JG3J;J#5B}g#su)2@VkEn;W zZ1Wmx-7L1rCjqLI-~=>FaL@sJntVAx&^flx(6Rc6&tE-I58L8C-YyV&jIv(hQJfxeXG+@GK>liuC8L=0JZ6XJ#uZd_3`Ivvu7YM@+pR54kZ~Q$k`|s$DirzKx7lsdu zKS0F!4btPheAP>Uu?ZlF*9_l7ib9@;;}jbMg5XmVEx@v9`B385e$2`33vwTwGGM{OXJnGa69_ zq6|bCh%yjmAj&|LfhYq}2BHl7Ut|DvG1mxO2li~?%TDY0W}0p8JO9n&h0{+nwb9^u zFx`NWA)1t;bzJt7uA}$}S4oZNLqvbf7pXgQ#rJ@ENTsBJMm>9q=nqom{Uhlgj6=(^ zrV6E^RrYMxvn*vDn>b-*9oL!4l|9FuIMJUk6`cutGVl1j#vCg%Yg=b>MLVB6@2Hu4 zWhz&+W=gqosiqrE`P^j2D3^@K)$qu%zJ9CA=rRsbOfeOw z182r#YL@7zuPZxqbSL8KI}$(o9Ox6gBG-3^id7zh{k%0?^mljlw@is+4^+L{pS+% z>ZzSa_8n}~%dDMb2I#m*Huc&$o=kl=K9Fo(XgZ!uKc8&vPo{d4iQ%OiBovJ(15pN| z3`7}-G7x1T%0QHXCX4m+ zqdviVNAUlCw_4I7Qt+TASP`7-6CUk?-{+(1Wr6n#Y!!%_Wku=|)E;`TPcoZ~!F2nWlTDkpCyWDM+e`ACD}9?t zdAPSNcF^ur%VH0(kqp+>8zS3C2J7t;Nn9ft`1s*HWNr%&u#p|`02|35)}P)ZX2e?i z&qFxr0i5%_NqtZako1(lZ*k(_+Q4rSdMdP#9us=)do2oFAIE65Zy_NHWmjfZrc{{8JD!s@IvPuGS1f1Qu4~U(PSJDc)EU<d##IgoWQ7{L_h(vuos1A=j)7Lvh%PBcXhF@ z>-RNkGk%IzVx0$Nl;;YbJxS1WeK?I-vE(_%RIy@AR&x35fm~J@`VtJ!ne~*R^P~CG zc6nME*|{Rw@}cJ{%{lA1&+>{nU;Gwoh2n; 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+ +int test_ctx_header(int argc, char **argv, const struct forkrun_ctx *ctx) { + if (ctx && ctx->version >= 1) { + printf("CTX_HEADER: batch=%lu worker=%u node=%u retries=%u bytes=%lu\n", + ctx->batch_index, ctx->worker_id, ctx->node_id, + ctx->num_kills, ctx->batch_byte_length); + } + return 0; +} diff --git a/UNIT_TESTS/c_plugin_test/test_ctx_header.so b/UNIT_TESTS/c_plugin_test/test_ctx_header.so new file mode 100755 index 0000000000000000000000000000000000000000..6fc94fba5fb70e9eafccc805fe61330bca80e8ef GIT binary patch literal 11840 zcmeHNU2Ggz6~5~vWZS0prkKVgZ8B|bi$@> zvyE+4N~9>zV5JJ>N1_!HFGx{es6a^YfV3qj3J;(F0`X8J3sK~#h#Db~TTqsB=ALgo zJ6%UrC3s=(YUkYZd(WJ?Gkeb2IXgNr){;mlj7{oEwT>w@AdKoKAi=c9)tz+Qt?mzG zx2&_?H@mq>lK@pp}=6^w?ODI%6iG&nx8Zq zVO35VFsa#rkL>51*o(qWkpm3QiD(S@d;K0Q5QROOtN^jzski*hhtWGJdTX*?6y7K6 z0m9GEkRHe7gAQD-Nm*~B>yVOo0b)<_y6yDk%R7GJwED)@N6&uk&y{WC9o8Sd>^^+* zhc6```Fq>$_pI}ONm@%=_S5CHE>!)N+70Xc&yrVF?cgCI)w&MTv2D))%^1(J`!|5pDL4+H%{TbF6$-Aju~J`GfDV%-&np z#Z~K#zaFvPSleVJu35jj<+qc8Z;OFsZF#0`&&awy`+lzf$HZ2ZhfiDQ`xkj?U3|;m zMy6ldr_{{pNRgYs3IX=sH#1V)i5Jw=6KpcTM z0&xW52*eSHBk=zm0o28)s|ON_OVI(Y3AgfhXz>fL9(nfdjbg<0pwWcs5=~0c1}?8- zG*C3cRZ=th7||cpA`QnpVcXRXm68G)_3UY)-$Rx6ccg!C7+SVHTPPLnvhR4lZ7cie z)NwoGdhTql?7QC7@!@=_=uSE5ysLT5Irj9tW6$J@PCmEjD&H;p_Ow55XI+PEsW~rK z^k>ve$$QSL6zxjcWvz~vFzRrA2Fm8nCFu}avhvQ7mO#hMwzt zIk(Ky^a917#qK1#?2|!Xw#j`3ier^&I5&!P1D@Em=?U(Iux~$lr&fEM;FZ-{?TZ9? zaF2pVVsTO>=2MAX+qNbzld(>svEDrC1gFxP8f)!1)^^vK3WF z``v=SDMi7@1xG!yOK@bkI|WBw!Z|Y!@c(hERtgAG=%5x@5uEE19^Ha-j?d#|4b)u% zI|QOuS&@1KHAj%6lMM2Cu19$6&_F#cMJnj8Z`Ta?c}3)?2nz<*qkq`~|1XO?{bLv4 zh$E%_0lp~wcLj%^V(xzi@PBu7!D|wz-w9;@$A^ax8QoMx?KOH2Qmxu+^!4;T*3;W} z!04WIGlu2(!r1?*y(G`E3N8~Vj}LYx4miDPS?mEelfmA4O=O$NV88uI0@q9iYkccA zGOz>K%no>f&1B%~_ip1ee67Fp5Dj_==Xh^cf2)N^!IbZ}7UJOCz;6?JDzcFt6ng!> z76qOq`Or=m*Ae9hilce7u8fm1N(~8`5iy3y(w#Oz1kB{1;Cq}q$ z$IGw><&vFsiWzR#jXZN=@c7YTqS7UR?KuI zm(T3aWt175hUvTWzA}Rt1^ld2&MGsrP$XL#`ko3n&%0hZS1L9jHt{?+@34Z*=JI6E zD`gztQD%MFIj=P5dj5hk-K<>MY=)G9X?OG`*6v`=hIkFK8TjKAa?|8PiB_S587!w4 zOP9;aq-|HA-K4z?PS$jM>HwxI6t3u=|1db`E#V&JM(=mQHun_6gC9S1s|D|tF&)nZ zK;%Wt;}O-rK(w&_>+-t-7nn(4&LNty^pUAx^KURQG3LOCYh$F|BeS`lSz2_L!2mW1}ur280 z_Zbj%1LULo?*|e64oV4l0DfMh^&|WT;U_eqcj-h}cQ)Q*lfF4MHqzTtb&_~{b_gt%Tp`Ztdea(ODh1bXb zLf7}`6$}mPN9Y5t5+|&Wd}&4WyX%^I0zJTYBl`G1FJ)-?==F}`oH(;BoImp1_6_tU z9NIV?Hxq$rxKF@ +#include + +int forkrun_use_ctx = 1; + +struct forkrun_ctx { + uint64_t batch_index; + uint64_t batch_offset; + uint64_t batch_byte_length; + uint32_t version; + uint32_t worker_id; + uint32_t node_id; + uint32_t num_kills; + uint32_t numa_major; + uint32_t numa_minor; + int32_t fd_in; + char delimiter; + char _pad[3]; +}; + +int test_ctx_naked(int argc, char **argv, const struct forkrun_ctx *ctx) { + if (ctx && ctx->version >= 1) { + printf("CTX_NAKED: batch=%lu worker=%u node=%u retries=%u bytes=%lu\n", + ctx->batch_index, ctx->worker_id, ctx->node_id, ctx->num_kills, + ctx->batch_byte_length); + } + return 0; +} diff --git a/UNIT_TESTS/c_plugin_test/test_ctx_naked.so b/UNIT_TESTS/c_plugin_test/test_ctx_naked.so new file mode 100755 index 0000000000000000000000000000000000000000..b09072778b04e32fc1a1f4d05ce0400e67599eb2 GIT binary patch literal 11840 zcmeHNUu+y_5&zCf$TdyvOK}sEw8_%g$O*|}J9Q{&P5s}O;H1HEq!t0oo_B4Za=x?n z_8Qwf5Gjh(U9U9?RsW*zcn;E+>l5pj7{o`Y7JAWR~Y5bK!Ryct8H}LtDexZ zTh>_XW_LFQBtVr4a9(3GPX&)cU-SUMXT49*Z{-PACV03Owl)NKyFlnM%6iGY0Y7Qh z!m^w+U@~B9AKA}Yu@{A{A_u6?iD(S@cl*&mAPPGIvI4|qx;b(`tOmv`jUS#{`@LqFO!lzj8OzNa3`?|9Av@4m+}2kxgY zucY62_qp^NtDDk^Tj@XE_nXPUt70HoS(BX+m#S^K)#s1dIH#*D9@7%9cI?Fm()i~G~L?2@b&I(Ek|iucW^yu)ZsWplTx&X%jS(5 zN`P>cRF6JP^d|$6n&UabcBow{B?UC<*|S7{lq&Dnq<`=%v@C0CrjWOazU}#zrL5!Q zCoRYI+^KBQcfIkG1Gz%p9k(+%H{jLhSQB%$HJQ!Zx$J_ge7ERZ6aJi)x6iqbn)R}I ze^N~rymMYDZEZHb(vjeH@lTk4fMk?aFp?H(iC-eX?OM^ zMRJz{cD3Jue!*2a&s8c~d4PUe=n8#~fUSVv{#-!d+Mllp#+?uyCYbk^5FN2*`cjBq z(+864!h1+s0W7YPA$nMTVEhH^RNt3|29FsT+n<>3Y0H(2^At(f>uD<)`GVsz^jzP| zx<#I5<|+IvwvFwwPX_(iCifL6j%B9d+$hpDcw*0{XSf%_zWwsOO66&S*HEZLq3+lPu&m26`s<$ia57Muf zZ0bEY-k6$d#ML22JmLt%5r`uYM<9+s9Dz6jaRlNBd<+ply%4PrkSBBP!DD*>)b}KL ze?;)VNm1}A!SViekKo8~cMFcXgmY#d;Q#x6rJxB?=%5x@798&++XdH2J}F$&N=iK} zutgwhm1U_%P;=-Uon(;Db3MXiR{+!tQlx_Z`i_7BKd*}%6=8Z{J$lQg{l6;m^u|u( zh$E%_8eb6p2ZF;-G54_nyzh=KcuNBHXMybh$iTocqn)a#14d^z6|0>_S4Y>;j?S(l zM*EoS7-`!V#^KK&AbF0JzD%S%($|_eVt1+~u?JXB27BwLB3n-e`|TeRxOy^JTl;Hjpam9TVUKh^^(9di69o7B==-;PFJ^z2Q0sZINPD;&w z5*F5AJv+Z4b^}%QxF(SP9ZeF7j7Wb2^tUvhUSs4UAVSW~$|#?D!eU+{{SU7Ax9g_+r$>${HGQD1_)Vp+@f zJbT`9^S(E)COvz`wVcw-%si=tFpDJp8qwNDnmM7!OE>SZkCrt&)^~Eq8ag$|Z986t z9Viy8X*=(5w{GyoQ++3o4-l0eS=LZm6w-rZM54wXR7Xai@9!J6o*y1QGc<0E_w|ns zkwNz5f!)BMtJfRu-9e@8QM#Mm-=K)+ouL#rbHoLx3fPIf%BGdk8-2$yI`Dqis8YJAG+0azntlKE&w7g zVjhpE{w1P?^=Ufmt@fTppXC0 zfT$ZFAKibyi0HRSUIF-3C<=uCApe>sjr2o0g?a|xHAdxu1OA?LIVXcY@~Kt%J{58# zq6cumKM|GBANtjN2H&X$YSkn3K=?aNxK@Hb@*aHWT9yk1JwWX1cStw9KHdx6-WRN3 z1fY6^KHv&*!urUUmPNn4su@h62lzomAMf*0Mj#)(-cg(rXSRj&N1offfxd(zFiywK zL|_{36EL73NiVf5%fQYfG{L>e^p?|nq<24t2Fie7fUbM~GaGwfL^PQGbb!4qOui4e ohDF@){NuV5=N@PT$Cdp7ydGIUf>I7zU;hVff&Tu8LIhR+12O5k{r~^~ literal 0 HcmV?d00001 diff --git a/forkrun_ring.c b/forkrun_ring.c index 2947e6b1..b51843f9 100644 --- a/forkrun_ring.c +++ b/forkrun_ring.c @@ -475,7 +475,7 @@ static __thread size_t tls_argv_cap = 0; // Shared tokenizer core. // If `arr` is non-NULL, it populates the Bash array. // If `arr` is NULL, it populates `tls_argv` starting at `fixed_argc`. -static int do_tokenize(int fd, size_t length, char delim, SHELL_VAR *arr, int fixed_argc, size_t *out_batch_argc) { +static int do_tokenize(int fd, size_t length, off_t offset, char delim, SHELL_VAR *arr, int fixed_argc, size_t *out_batch_argc) { if (length == 0) { if (out_batch_argc) *out_batch_argc = 0; return EXECUTION_SUCCESS; @@ -494,7 +494,7 @@ static int do_tokenize(int fd, size_t length, char delim, SHELL_VAR *arr, int fi size_t total_read = 0; while (total_read < length) { - ssize_t n = pread(fd, tls_map_buf + total_read, length - total_read, tls_batch_offset + total_read); + ssize_t n = pread(fd, tls_map_buf + total_read, length - total_read, offset + total_read); if (n < 0) { if (errno == EINTR) continue; return EXECUTION_FAILURE; @@ -502,7 +502,7 @@ static int do_tokenize(int fd, size_t length, char delim, SHELL_VAR *arr, int fi if (n == 0) break; // EOF reached before expected length total_read += n; } - + // If we couldn't fulfill the exact claimed length, the batch is broken. if (total_read < length) return EXECUTION_FAILURE; @@ -566,37 +566,37 @@ static int ring_map_main(int argc, char **argv) { if (find_variable(arr_name)) { unbind_variable(arr_name); } - + SHELL_VAR *v = make_new_array_variable(arr_name); if (!v) return EXECUTION_FAILURE; - return do_tokenize(fd, length, delim, v, 0, NULL); + return do_tokenize(fd, length, tls_batch_offset, delim, v, 0, NULL); } // Returns 0 (true) if safe to execute directly via posix_spawnp (Binary or Shebang) // Returns 1 (false) if it is a text script without a shebang (needs Bash AST parsing) static int ring_is_spawnable_main(int argc, char **argv) { if (argc < 2) return EXECUTION_FAILURE; - + int fd = open(argv[1], O_RDONLY); if (fd < 0) return EXECUTION_FAILURE; // File not found/unreadable -> Let Bash handle it - + unsigned char buf[1024]; ssize_t n = read(fd, buf, sizeof(buf)); close(fd); - + if (n <= 0) return EXECUTION_FAILURE; - + // 1. Shebang: The kernel handles this perfectly via binfmt_script if (n >= 2 && buf[0] == '#' && buf[1] == '!') return EXECUTION_SUCCESS; - + // 2. Binary Heuristic: Any file containing a NULL byte in the first 1KB is a compiled binary. // Text scripts cannot contain NULL bytes. This catches ELF, Mach-O, WASM, etc., instantly. for (ssize_t i = 0; i < n; i++) { if (buf[i] == '\0') return EXECUTION_SUCCESS; } - - // 3. Pure text without a shebang. + + // 3. Pure text without a shebang. // posix_spawnp might choke or pass it to /bin/sh (breaking Bashisms). // Return failure to enforce ring_map fallback! return EXECUTION_FAILURE; @@ -605,6 +605,14 @@ static int ring_is_spawnable_main(int argc, char **argv) { // --------------------------------------------------------- // ring_exec: Ultra-fast path for external binaries // --------------------------------------------------------- +// Superscalar prefetch pipeline: +// ring_claim → commits prefetched_batch to TLS globals (or blocks for N) +// ring_exec → (a) tokenizes N (or skips if pre-tokenized), +// (b) spawns child N, +// (c) non-blocking claims N+1 while child runs, +// (d) pre-tokenizes N+1 (overwriting tls_argv safely), +// (e) waits for child N, +// (f) shadow-orphan-rescues N+1 if child N failed. static int ring_exec_main(int argc, char **argv) { // Usage: ring_exec [fixed_args...] if (argc < 5) return EXECUTION_FAILURE; @@ -612,7 +620,7 @@ static int ring_exec_main(int argc, char **argv) { int fd = atoi(argv[1]); size_t length = (size_t)atoll(argv[2]); char delim = argv[3][0]; - + int fixed_argc = argc - 4; // 1. Ensure baseline capacity for fixed arguments @@ -628,47 +636,98 @@ static int ring_exec_main(int argc, char **argv) { tls_argv[i] = argv[4 + i]; } - // 3. Tokenize batch directly into tls_argv - size_t batch_argc = 0; - int ret = do_tokenize(fd, length, delim, NULL, fixed_argc, &batch_argc); - if (ret != EXECUTION_SUCCESS) return ret; - - // 4. Terminate argv array for execve - tls_argv[fixed_argc + batch_argc] = NULL; + // 3. TOKENIZE BATCH N + // If the previous cycle's overlap already tokenized this batch, skip parsing + // entirely — the kernel copied argv into the child at spawn, so tls_argv and + // tls_map_buf still hold N+1's data from last cycle, which IS batch N now. + if (!prefetch_tokens_ready) { + size_t batch_argc = 0; + int ret = do_tokenize(fd, length, tls_batch_offset, delim, NULL, fixed_argc, &batch_argc); + if (ret != EXECUTION_SUCCESS) return ret; + tls_argv[fixed_argc + batch_argc] = NULL; + } else { + // Perfect cache hit — bypass tokenization entirely. + prefetch_tokens_ready = false; + } - // 5. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) + // 4. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) sigset_t set, oset; sigemptyset(&set); sigaddset(&set, SIGCHLD); sigprocmask(SIG_BLOCK, &set, &oset); - // 6. Spawn the child (inherits FDs natively) + // 5. SPAWN CHILD N (returns immediately; child runs concurrently with prefetch below) pid_t pid; - ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); + int ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); + + // 6. THE LATENCY HIDING OVERLAP + // Child N is now running. Use its execution time to prefetch and pre-tokenize + // Batch N+1. This is non-blocking: if the ring has no data yet (scanner is still + // ingesting), do_lockfree_claim returns 1 and we degrade gracefully to zero overhead. + if (ret == 0 && state && !atomic_load_relaxed(&state[0].emergency_abort)) { + if (do_lockfree_claim(&prefetched_batch, false) == 0) { + have_prefetch = true; + // Pre-tokenize N+1 directly into tls_argv. Safe because posix_spawnp + // already copied argv into the child's address space — the parent's + // tls_argv is free to be overwritten. + size_t next_argc = 0; + if (do_tokenize(fd, prefetched_batch.length, (off_t)prefetched_batch.offset, + delim, NULL, fixed_argc, &next_argc) == EXECUTION_SUCCESS) { + tls_argv[fixed_argc + next_argc] = NULL; + prefetch_tokens_ready = true; + } + // If tokenize failed, have_prefetch stays true but prefetch_tokens_ready + // stays false. ring_exec will re-tokenize next cycle (safe fallback). + } + // ret 1 = no data yet, ret 2 = EOF: have_prefetch stays false. + // ring_claim_main will do a synchronous blocking claim next iteration. + } - // 7. Wait for the child synchronously + // 7. WAIT FOR CHILD N int status = 0; if (ret == 0) { while (waitpid(pid, &status, 0) == -1) { - if (errno != EINTR) { - ret = -1; // Mark the execution as failed! - break; - } + if (errno != EINTR) { ret = -1; break; } } } // 8. Restore signal mask sigprocmask(SIG_SETMASK, &oset, NULL); - if (ret != 0) return EXECUTION_FAILURE; - - // Return exact status correctness (crucial for -E auto-retry) - if (WIFEXITED(status)) { - return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); - } - if (WIFSIGNALED(status)) { - return 128 + WTERMSIG(status); // Standard shell convention for fatal signals + // 9. THE SHADOW ORPHAN RESCUE + // Child N failed. We already atomically claimed N+1 from the ring — if we just + // return failure, that batch is gone forever. Escrow it so the Bash retry trap + // can safely reprocess N while N+1 waits in the pipe for the next worker. + bool child_failed = (ret != 0) || + (WIFEXITED(status) && WEXITSTATUS(status) != 0) || + WIFSIGNALED(status); + + if (child_failed && have_prefetch) { + int node = (my_numa_node >= 0) ? my_numa_node : 0; + if (fd_escrow_w && fd_escrow_w[node] >= 0) { + struct EscrowPacket ep = { + .idx = prefetched_batch.idx, + .cnt = prefetched_batch.cnt, + .num_kills = prefetched_batch.num_kills + }; + ssize_t ew; + do { + ew = write(fd_escrow_w[node], &ep, sizeof(ep)); + } while (ew < 0 && errno == EINTR); + if (ew == sizeof(ep)) { + uint64_t one = 1; + sys_write(evfd_data_arr[node], &one, 8); + tl_drain_escrow = true; + } + } + have_prefetch = false; + prefetch_tokens_ready = false; } + + // 10. RETURN + if (ret != 0) return EXECUTION_FAILURE; + if (WIFEXITED(status)) return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); + if (WIFSIGNALED(status)) return 128 + WTERMSIG(status); return EXECUTION_FAILURE; } @@ -698,7 +757,7 @@ static int ring_exec_splice_main(int argc, char **argv) { // 2. Create the pipe int pfd[2]; if (pipe(pfd) != 0) return EXECUTION_FAILURE; - + // Optional: Maximize pipe buffer size for throughput fcntl(pfd[1], F_SETPIPE_SZ, 1048576); @@ -726,7 +785,7 @@ static int ring_exec_splice_main(int argc, char **argv) { if (ret == 0) { // IGNORE SIGPIPE so 'head -n' doesn't kill the worker! void (*old_handler)(int) = signal(SIGPIPE, SIG_IGN); - + size_t written = 0; off_t offset = tls_batch_offset; while (written < length) { @@ -738,11 +797,11 @@ static int ring_exec_splice_main(int argc, char **argv) { if (s == 0) break; written += s; } - + // Restore previous SIGPIPE handler signal(SIGPIPE, old_handler); } - + // 8. Close the write end to send EOF to the child close(pfd[1]); @@ -1060,6 +1119,25 @@ static inline uint64_t fast_log2(uint64_t v) { // 2. TLS AND SHARED STATE // ============================================================================== +// ------------------------------------------------------------------ +// SUPERSCALAR PREFETCH STATE +// ------------------------------------------------------------------ +struct WorkerBatchState { + uint64_t idx; + uint64_t cnt; + uint32_t num_kills; + uint64_t offset; + uint64_t length; + uint32_t major; + uint32_t minor; +}; + +static __thread struct WorkerBatchState prefetched_batch; +static __thread bool have_prefetch = false; +static __thread bool prefetch_tokens_ready = false; +static __thread size_t prefetch_batch_argc = 0; +static __thread bool tl_drain_escrow = true; + static __thread int my_numa_node = -1; static __thread bool is_waiting_on_ring = false; static __thread off_t last_ack_offset = 0; @@ -1073,7 +1151,6 @@ static __thread uint32_t worker_last_num_kills = 0; static __thread uint64_t tl_remainder_idx = 0; static __thread uint64_t tl_remainder_cnt = 0; static __thread uint32_t tl_remainder_kills = 0; -static __thread bool tl_recently_escrowed = false; static int *evfd_data_arr = NULL; static int *evfd_eof_arr = NULL; @@ -1939,7 +2016,7 @@ static int ring_init_main(int argc, char **argv) { eventfd(0, EFD_CLOEXEC | EFD_NONBLOCK | EFD_SEMAPHORE); evfd_meta_arr[n] = eventfd(0, EFD_CLOEXEC | EFD_NONBLOCK | EFD_SEMAPHORE); - if (evfd_data_arr[n] < 0 || evfd_eof_arr[n] < 0 || + if (evfd_data_arr[n] < 0 || evfd_eof_arr[n] < 0 || evfd_indexer_arr[n] < 0 || evfd_meta_arr[n] < 0) { builtin_error("forkrun: eventfd creation failed (FD limit reached?)"); ring_destroy_main(0, NULL); @@ -3955,128 +4032,55 @@ static int ring_numa_scanner_main(int argc, char **argv) { // 7. CONSUMERS (Claim, Ack, Order) // ============================================================================== -// Workers Claiming Data (Inertial Particles): -// The fast path is a single lock-free `atomic_fetch_add` to claim a batch of -// records. There are NO CAS retry loops on the fast path. If a worker -// overshoots and claims records that haven't arrived yet (inertia), it -// processes the available ones and deposits the remainder into an escrow pipe -// for other idle workers to steal. Escrow is pure advisory capability; forward -// progress is guaranteed by strictly monotonic indices. -static int ring_claim_main(int argc, char **argv) { - const char *v_target = "REPLY"; - - if (argc >= 2) { - v_target = argv[1]; - } - - if (my_numa_node == -1) { - const char *s_node = get_string_value("RING_NODE_ID"); - if (s_node) { - my_numa_node = atoi(s_node); - } else { - int phys = auto_detect_numa_node(); - my_numa_node = 0; - bool found = false; - if (g_logical_to_phys_map) { - for (uint32_t i = 0; i < global_num_nodes; i++) { - if (g_logical_to_phys_map[i] == (uint32_t)phys) { - my_numa_node = i; - found = true; - break; - } - } - } - if (!found && g_debug && global_num_nodes > 1) { - fprintf(stderr, - "forkrun[DEBUG] Worker on unmapped physical node %d, " - "defaulting to logical 0\n", - phys); - } - } - if (my_numa_node >= (int)global_num_nodes) - my_numa_node = 0; - } +// ------------------------------------------------------------------ +// do_lockfree_claim: Pure side-effect-free batch claim helper. +// Populates `out` with batch metadata without touching Bash variables. +// Returns: 0=success, 1=no data now (non-blocking), 2=EOF, EXECUTION_FAILURE=error +// ------------------------------------------------------------------ +static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { struct SharedState *local_state = &state[my_numa_node]; - uint64_t my_read_idx; uint64_t claim_count = 1; uint32_t current_kills = 0; int spin = 0; - // --- UNIVERSAL SIGPIPE / TEARDOWN SHIELD --- - if (state) { - // 1. Did someone else pull the fire alarm? (e.g., ring_order, or Fallow dying) - if (atomic_load_relaxed(&state[0].emergency_abort)) { - return EXECUTION_FAILURE; - } - - // 2. Sentry duty: Check if stdout is broken (Crucial for -u realtime mode) - // We only poll every 64 claims to ensure absolute zero overhead on the fast path. - static __thread int claim_calls = 0; - if ((claim_calls++ & 63) == 0) { - struct pollfd pfd_stdout = {.fd = 1, .events = POLLOUT}; - if (poll(&pfd_stdout, 1, 0) > 0 && (pfd_stdout.revents & (POLLERR | POLLHUP))) { - // The downstream pipe was cut (e.g., head -n 5). Pull the fire alarm! - pull_fire_alarm(); - return EXECUTION_FAILURE; - } - } - } - // ------------------------------------------- + if (atomic_load_relaxed(&state[0].emergency_abort)) + return EXECUTION_FAILURE; + // TLS remainder fast-path if (tl_remainder_cnt > 0) { my_read_idx = tl_remainder_idx; claim_count = tl_remainder_cnt; current_kills = tl_remainder_kills; tl_remainder_cnt = 0; - goto check_boundaries; + goto dlc_check_boundaries; } -restart_loop: +dlc_restart_loop: - // NEW: ESCROW PRIORITY INVERSION (Head-of-line blocking prevention) - // If this specific worker just dropped a partial batch into escrow, - // it prioritizes getting it back before touching the main ring. - if (tl_recently_escrowed) { - tl_recently_escrowed = false; - if (fd_escrow_r && fd_escrow_r[my_numa_node] >= 0) { - struct EscrowPacket ep; - ssize_t er; - do { - er = read(fd_escrow_r[my_numa_node], &ep, sizeof(ep)); - } while (er < 0 && errno == EINTR); - if (er == sizeof(ep)) { - my_read_idx = ep.idx; - claim_count = ep.cnt; - current_kills = ep.num_kills; - - // --- NEW: Export state --- - char buf[32]; - snprintf(buf, sizeof(buf), "%u", ep.num_kills); - bind_variable("RING_NUM_KILLS", buf, 0); - - int limit = 3; // Default to 3 retries - const char *s_lim = get_string_value("FORKRUN_RETRY_LIMIT"); - if (s_lim) limit = atoi(s_lim); - - // If limit is negative, we allow infinite retries (never poison) - // If limit is >= 0, we poison the batch when kills reaches the limit - if (limit >= 0 && ep.num_kills >= (uint32_t)limit) { - bind_variable("RING_POISONED", "1", 0); - } else { - bind_variable("RING_POISONED", "0", 0); - } - // ------------------------ - - // Safely jump to the write_idx check block. If this is an - // overshoot packet, we MUST wait for the scanner to publish it! - goto evaluate_claim; - } - } + // Escrow continuous drain: vacuums the pipe until it is empty, then snaps + // back to the lock-free fast path. tl_drain_escrow stays true as long as + // packets keep arriving; only set false on EAGAIN (pipe empty). + if (tl_drain_escrow && fd_escrow_r && fd_escrow_r[my_numa_node] >= 0) { + struct EscrowPacket ep; + ssize_t er; + do { + er = read(fd_escrow_r[my_numa_node], &ep, sizeof(ep)); + } while (er < 0 && errno == EINTR); + if (er == sizeof(ep)) { + my_read_idx = ep.idx; + claim_count = ep.cnt; + current_kills = ep.num_kills; + // Do NOT clear tl_drain_escrow here — keep draining until pipe is empty. + goto dlc_evaluate_claim; + } else if (er < 0 && (errno == EAGAIN || errno == EWOULDBLOCK)) { + // Pipe is fully drained. Snap back to zero-overhead fast path. + tl_drain_escrow = false; + } } while (1) { - // 1. Ring check FIRST (Local Work) + // 1. Ring check (Local Work) uint64_t w_snap = atomic_load_acquire(&local_state->write_idx); uint64_t r_curr = atomic_load_relaxed(&local_state->read_idx); @@ -4100,7 +4104,7 @@ static int ring_claim_main(int argc, char **argv) { claim_count = w_snap - r_curr; if (claim_count > 1) { - uint64_t safe_count = claim_count; // <--- CRITICAL FIX: Default to full claim + uint64_t safe_count = claim_count; for (uint64_t i = 0; i < claim_count; i++) { if (local_state->stride_ring[(r_curr + i) & RING_MASK] & FLAG_CHUNK_BOUNDARY) { @@ -4114,7 +4118,6 @@ static int ring_claim_main(int argc, char **argv) { my_read_idx = __atomic_fetch_add(&local_state->read_idx, claim_count, __ATOMIC_SEQ_CST); - // --- NEW: Export state --- if (!local_state->numa_enabled) { int64_t sbatch_check = atomic_load_relaxed(&local_state->signed_batch_size); @@ -4130,7 +4133,7 @@ static int ring_claim_main(int argc, char **argv) { break; } - // 2. Escrow check SECOND (Non-Local Work) + // 2. Escrow check (Non-Local Work) if (fd_escrow_r && fd_escrow_r[my_numa_node] >= 0) { struct EscrowPacket ep; ssize_t er; @@ -4141,54 +4144,28 @@ static int ring_claim_main(int argc, char **argv) { my_read_idx = ep.idx; claim_count = ep.cnt; current_kills = ep.num_kills; - - // --- NEW: Export state --- - char buf[32]; - snprintf(buf, sizeof(buf), "%u", ep.num_kills); - bind_variable("RING_NUM_KILLS", buf, 0); - - u64toa(ep.idx, buf); - bind_variable("RING_BATCH_IDX", buf, 0); - - int limit = 3; // Default to 3 retries - const char *s_lim = get_string_value("FORKRUN_RETRY_LIMIT"); - if (s_lim) limit = atoi(s_lim); - - // If limit is negative, we allow infinite retries (never poison) - // If limit is >= 0, we poison the batch when kills reaches the limit - if (limit >= 0 && ep.num_kills >= (uint32_t)limit) { - bind_variable("RING_POISONED", "1", 0); - } else { - bind_variable("RING_POISONED", "0", 0); - } - // ------------------------ - break; } } - // 3. Scanner finished check THIRD (The 3 Sequential Conditions for EOF) - // CONDITION 1: Has the supplier declared EOF permanently? + // 3. Scanner finished check (EOF) if (atomic_load_acquire(&local_state->scanner_finished)) { - - // CONDITION 2: Re-verify local work is empty AFTER observing Supplier EOF if (atomic_load_acquire(&local_state->read_idx) < atomic_load_acquire(&local_state->write_idx)) { continue; } - - // CONDITION 3: Re-verify non-local work (Escrow) is empty AFTER Cond 1 & 2 if (fd_escrow_r && fd_escrow_r[my_numa_node] >= 0) { struct pollfd pfd = {.fd = fd_escrow_r[my_numa_node], .events = POLLIN}; if (poll(&pfd, 1, 0) > 0 && (pfd.revents & POLLIN)) { continue; } } - - // All 3 physical conditions are met in order. Consensus achieved. Terminate. - return 2; + return 2; // EOF } + // Non-blocking mode: return immediately if no data + if (!blocking) return 1; + // 4. Spin if (spin < 100) { cpu_relax(); @@ -4200,7 +4177,6 @@ static int ring_claim_main(int argc, char **argv) { __atomic_fetch_add(&local_state->active_waiters, 1, __ATOMIC_SEQ_CST); is_waiting_on_ring = true; - // RULE: 3-way simultaneous poll struct pollfd pfds[3] = { {.fd = evfd_data_arr[my_numa_node], .events = POLLIN}, {.fd = (fd_escrow_r && fd_escrow_r[my_numa_node] >= 0) ? fd_escrow_r[my_numa_node] : -1, .events = POLLIN}, @@ -4208,7 +4184,6 @@ static int ring_claim_main(int argc, char **argv) { }; while (1) { - // RULE: Must simultaneously poll until parent EOF + empty local work is verified if (atomic_load_acquire(&local_state->write_idx) > atomic_load_relaxed(&local_state->read_idx)) break; @@ -4218,7 +4193,6 @@ static int ring_claim_main(int argc, char **argv) { poll(pfds, 3, -1); - // EMERGENCY BYPASS: If someone pulled the fire alarm while we slept, exit immediately if (atomic_load_relaxed(&state[0].emergency_abort)) { cleanup_waiter_state(); return EXECUTION_FAILURE; @@ -4228,20 +4202,14 @@ static int ring_claim_main(int argc, char **argv) { bool escrow_fired = (pfds[1].fd >= 0 && (pfds[1].revents & POLLIN) != 0); bool eof_fired = (pfds[2].revents & POLLIN) != 0; - // RULE: Strict checking order - // 1. check if the "local work evfd" was non-zero. if so consume it and loop back. if (data_fired) { uint64_t v; sys_read(pfds[0].fd, &v, 8); continue; - } - // 2. check if the non-local work evfd was non-zero. if so consume it and loop back. - else if (escrow_fired) { - break; // Break so outer loop's Escrow Check processes it - } - // 3. check if EOF evfd was non-zero. exit ONLY when EOF is nonzero and work evfds are zero - else if (eof_fired && !data_fired && !escrow_fired) { - break; // Break so outer loop's Scanner Finished check triggers safe exit + } else if (escrow_fired) { + break; + } else if (eof_fired && !data_fired && !escrow_fired) { + break; } } @@ -4249,88 +4217,82 @@ static int ring_claim_main(int argc, char **argv) { spin = 0; } -evaluate_claim: - uint64_t w_curr = atomic_load_acquire(&local_state->write_idx); - if (my_read_idx + claim_count > w_curr) { - if (atomic_load_acquire(&local_state->scanner_finished)) { - w_curr = atomic_load_acquire(&local_state->write_idx); - int64_t diff = (int64_t)w_curr - (int64_t)my_read_idx; - if (diff < 0) - diff = 0; - if ((uint64_t)diff < claim_count) - claim_count = (uint64_t)diff; - - if (claim_count == 0) { - spin = 0; - goto restart_loop; - } - } else { - __atomic_fetch_add(&local_state->active_waiters, 1, __ATOMIC_SEQ_CST); - is_waiting_on_ring = true; - while (1) { +dlc_evaluate_claim: + { + uint64_t w_curr = atomic_load_acquire(&local_state->write_idx); + if (my_read_idx + claim_count > w_curr) { + if (atomic_load_acquire(&local_state->scanner_finished)) { w_curr = atomic_load_acquire(&local_state->write_idx); - if (w_curr > my_read_idx) { - uint64_t avail = w_curr - my_read_idx; - if (avail < claim_count) { - struct EscrowPacket ep = {.idx = my_read_idx + avail, - .cnt = claim_count - avail, - .num_kills = current_kills}; - ssize_t ew; - do { - ew = write(fd_escrow_w[my_numa_node], &ep, sizeof(ep)); - } while (ew < 0 && errno == EINTR); - if (ew == sizeof(ep)) { - claim_count = avail; - uint64_t one = 1; - sys_write(evfd_data_arr[my_numa_node], &one, 8); + int64_t diff = (int64_t)w_curr - (int64_t)my_read_idx; + if (diff < 0) diff = 0; + if ((uint64_t)diff < claim_count) claim_count = (uint64_t)diff; + + if (claim_count == 0) { + spin = 0; + goto dlc_restart_loop; + } + } else { + __atomic_fetch_add(&local_state->active_waiters, 1, __ATOMIC_SEQ_CST); + is_waiting_on_ring = true; + while (1) { + w_curr = atomic_load_acquire(&local_state->write_idx); + if (w_curr > my_read_idx) { + uint64_t avail = w_curr - my_read_idx; + if (avail < claim_count) { + struct EscrowPacket ep = {.idx = my_read_idx + avail, + .cnt = claim_count - avail, + .num_kills = current_kills}; + ssize_t ew; + do { + ew = write(fd_escrow_w[my_numa_node], &ep, sizeof(ep)); + } while (ew < 0 && errno == EINTR); + if (ew == sizeof(ep)) { + claim_count = avail; + uint64_t one = 1; + sys_write(evfd_data_arr[my_numa_node], &one, 8); + break; + } + } else { break; } - } else { + } + if (atomic_load_acquire(&local_state->scanner_finished)) { + w_curr = atomic_load_acquire(&local_state->write_idx); + int64_t diff = (int64_t)w_curr - (int64_t)my_read_idx; + if (diff < 0) diff = 0; + if ((uint64_t)diff < claim_count) claim_count = (uint64_t)diff; break; } - } - if (atomic_load_acquire(&local_state->scanner_finished)) { - w_curr = atomic_load_acquire(&local_state->write_idx); - int64_t diff = (int64_t)w_curr - (int64_t)my_read_idx; - if (diff < 0) - diff = 0; - if ((uint64_t)diff < claim_count) - claim_count = (uint64_t)diff; - break; - } + struct pollfd pfds[2] = { + {.fd = evfd_data_arr[my_numa_node], .events = POLLIN}, + {.fd = evfd_eof_arr[my_numa_node], .events = POLLIN}}; - struct pollfd pfds[2] = { - {.fd = evfd_data_arr[my_numa_node], .events = POLLIN}, - {.fd = evfd_eof_arr[my_numa_node], .events = POLLIN}}; + poll(pfds, 2, -1); - poll(pfds, 2, -1); + if (atomic_load_relaxed(&state[0].emergency_abort)) { + cleanup_waiter_state(); + return EXECUTION_FAILURE; + } - // EMERGENCY BYPASS: If someone pulled the fire alarm while we slept, exit immediately - if (atomic_load_relaxed(&state[0].emergency_abort)) { - cleanup_waiter_state(); - return EXECUTION_FAILURE; + bool data_fired = (pfds[0].revents & POLLIN) != 0; + if (data_fired) { + uint64_t v; + sys_read(evfd_data_arr[my_numa_node], &v, 8); + } } - - bool data_fired = (pfds[0].revents & POLLIN) != 0; - - if (data_fired) { - uint64_t v; - sys_read(evfd_data_arr[my_numa_node], &v, 8); - // Let loop naturally re-evaluate w_curr + cleanup_waiter_state(); + if (claim_count == 0) { + spin = 0; + goto dlc_restart_loop; } } - cleanup_waiter_state(); - if (claim_count == 0) { - spin = 0; - goto restart_loop; - } } } -check_boundaries: +dlc_check_boundaries: if (claim_count > 1) { - uint64_t safe_count = claim_count; // <--- CRITICAL FIX: Default to full claim + uint64_t safe_count = claim_count; for (uint64_t i = 0; i < claim_count; i++) { if (local_state->stride_ring[(my_read_idx + i) & RING_MASK] & FLAG_CHUNK_BOUNDARY) { @@ -4355,48 +4317,143 @@ static int ring_claim_main(int argc, char **argv) { } else if (ew == sizeof(ep)) { uint64_t one = 1; sys_write(evfd_data_arr[my_numa_node], &one, 8); - - // NEW: We successfully dropped into escrow. Flag ourselves to pick it up ASAP. - tl_recently_escrowed = true; + tl_drain_escrow = true; } claim_count = safe_count; } } - uint64_t final_val = 0; - - // We ALWAYS return bytes now. Line count is exported via RING_BATCH_SLOTS. + // Populate output struct uint64_t start = local_state->offset_ring[my_read_idx & RING_MASK]; uint64_t end = local_state->end_ring[(my_read_idx + claim_count - 1) & RING_MASK]; - final_val = end - start; - // The number of ring slots claimed is ALWAYS the logical line/chunk count + out->idx = my_read_idx; + out->cnt = claim_count; + out->num_kills = current_kills; + out->offset = start; + out->length = end - start; + + if (local_state->numa_enabled) { + out->major = local_state->major_ring[my_read_idx & RING_MASK]; + out->minor = local_state->minor_ring[my_read_idx & RING_MASK] & ~FLAG_MAJOR_EOF; + if (local_state->minor_ring[(my_read_idx + claim_count - 1) & RING_MASK] & + FLAG_MAJOR_EOF) { + out->minor |= FLAG_MAJOR_EOF; + } + } else { + out->major = 0; + out->minor = 0; + } + __atomic_fetch_add(&local_state->total_lines_consumed, claim_count, __ATOMIC_SEQ_CST); - worker_last_idx = my_read_idx; - worker_last_cnt = claim_count; - worker_last_num_kills = current_kills; + return 0; +} + +// ring_claim: Superscalar-aware batch claim with prefetch consumption. +// If a prefetched batch is available from the previous ring_exec overlap, +// consumes it directly. Otherwise, calls do_lockfree_claim synchronously. +// All Bash variable bindings are centralized here. +static int ring_claim_main(int argc, char **argv) { + const char *v_target = "REPLY"; + + if (argc >= 2) { + v_target = argv[1]; + } + + if (my_numa_node == -1) { + const char *s_node = get_string_value("RING_NODE_ID"); + if (s_node) { + my_numa_node = atoi(s_node); + } else { + int phys = auto_detect_numa_node(); + my_numa_node = 0; + bool found = false; + if (g_logical_to_phys_map) { + for (uint32_t i = 0; i < global_num_nodes; i++) { + if (g_logical_to_phys_map[i] == (uint32_t)phys) { + my_numa_node = i; + found = true; + break; + } + } + } + if (!found && g_debug && global_num_nodes > 1) { + fprintf(stderr, + "forkrun[DEBUG] Worker on unmapped physical node %d, " + "defaulting to logical 0\n", + phys); + } + } + if (my_numa_node >= (int)global_num_nodes) + my_numa_node = 0; + } + + // --- UNIVERSAL SIGPIPE / TEARDOWN SHIELD --- + if (state) { + if (atomic_load_relaxed(&state[0].emergency_abort)) { + return EXECUTION_FAILURE; + } + + static __thread int claim_calls = 0; + if ((claim_calls++ & 63) == 0) { + struct pollfd pfd_stdout = {.fd = 1, .events = POLLOUT}; + if (poll(&pfd_stdout, 1, 0) > 0 && (pfd_stdout.revents & (POLLERR | POLLHUP))) { + pull_fire_alarm(); + return EXECUTION_FAILURE; + } + } + } + // ------------------------------------------- + + struct WorkerBatchState batch; + int rc; + + if (have_prefetch) { + // Consume the prefetched batch from the previous ring_exec overlap + batch = prefetched_batch; + have_prefetch = false; + rc = 0; + } else { + // Synchronous blocking claim + rc = do_lockfree_claim(&batch, true); + } + if (rc != 0) return rc; + + // --- Publish metadata to TLS globals --- + worker_last_idx = batch.idx; + worker_last_cnt = batch.cnt; + worker_last_num_kills = batch.num_kills; + worker_last_major = batch.major; + worker_last_minor = batch.minor; + tls_batch_offset = (off_t)batch.offset; + + // --- Bind the byte-length to the target Bash variable --- char buf[64]; - u64toa(final_val, buf); + u64toa(batch.length, buf); bind_var_or_array(v_target, buf, 0); - uint64_t start_offset = - local_state->offset_ring[my_read_idx & RING_MASK]; + // --- Export escrow/poison metadata if this was a recycled batch --- + if (batch.num_kills > 0) { + snprintf(buf, sizeof(buf), "%u", batch.num_kills); + bind_variable("RING_NUM_KILLS", buf, 0); - if (local_state->numa_enabled) { - worker_last_major = local_state->major_ring[my_read_idx & RING_MASK]; - worker_last_minor = - local_state->minor_ring[my_read_idx & RING_MASK] & ~FLAG_MAJOR_EOF; + u64toa(batch.idx, buf); + bind_variable("RING_BATCH_IDX", buf, 0); - if (local_state->minor_ring[(my_read_idx + claim_count - 1) & RING_MASK] & - FLAG_MAJOR_EOF) { - worker_last_minor |= FLAG_MAJOR_EOF; + int limit = 3; + const char *s_lim = get_string_value("FORKRUN_RETRY_LIMIT"); + if (s_lim) limit = atoi(s_lim); + + if (limit >= 0 && batch.num_kills >= (uint32_t)limit) { + bind_variable("RING_POISONED", "1", 0); + } else { + bind_variable("RING_POISONED", "0", 0); } } - tls_batch_offset = (off_t)start_offset; return 0; } @@ -5040,7 +5097,7 @@ static int ring_lseek_main(int argc, char **argv) { if (argc < 3 || argc > 5) return EXECUTION_FAILURE; int fd = atoi(argv[1]); - + // ZERO-OVERHEAD TLS INJECTION: Support '-' to auto-grab the batch offset off_t off; if (argv[2][0] == '-' && argv[2][1] == '\0') { @@ -5048,7 +5105,7 @@ static int ring_lseek_main(int argc, char **argv) { } else { off = atoll(argv[2]); } - + int whence = SEEK_CUR; if (argc > 3) { if (!strcmp(argv[3], "SEEK_SET")) @@ -5691,7 +5748,7 @@ static int ring_escrow_put_main(int argc, char **argv) { uint64_t idx; if (argv[2][0] == '-' && argv[2][1] == '\0') idx = worker_last_idx; else idx = strtoull(argv[2], NULL, 10); - + uint64_t cnt; if (argv[3][0] == '-' && argv[3][1] == '\0') cnt = worker_last_cnt; else cnt = strtoull(argv[3], NULL, 10); @@ -5783,7 +5840,7 @@ static int ring_set_resume_main(int argc, char **argv) { g_state->is_resume_mode = 1; g_state->resume_horizon = strtoull(argv[1], NULL, 10); g_state->resume_jagged_count = 0; - + for (int i = 2; i < argc && g_state->resume_jagged_count < 1024; i++) { char *colon = strchr(argv[i], ':'); if (colon) { @@ -5904,7 +5961,7 @@ static int ring_poll_main(int argc, char **argv) { // If there is no core infrastructure left to poll, exit if (core_cnt == 0 && g_poll_deadline_ms == 0) { free(pfds); free(meta); - return EXECUTION_FAILURE; + return EXECUTION_FAILURE; } int r; @@ -5913,7 +5970,7 @@ static int ring_poll_main(int argc, char **argv) { free(pfds); free(meta); return EXECUTION_FAILURE; } - + int timeout_this_iter = 100; // 100ms default for fire alarm checks if (g_poll_deadline_ms > 0) { uint64_t now_ms = get_mono_ms(); @@ -5927,7 +5984,7 @@ static int ring_poll_main(int argc, char **argv) { timeout_this_iter = (remaining_ms < 100) ? (int)remaining_ms : 100; if (timeout_this_iter < 1) timeout_this_iter = 1; } - + r = poll(pfds, p_cnt, timeout_this_iter); } while (r == 0 || (r < 0 && errno == EINTR)); @@ -5939,7 +5996,7 @@ static int ring_poll_main(int argc, char **argv) { // 4. Process the Events for (int i = 0; i < p_cnt; i++) { if (pfds[i].revents & (POLLIN | POLLHUP | POLLERR)) { - if (meta[i].type == 0 || meta[i].type == 3) { + if (meta[i].type == 0 || meta[i].type == 3) { // --- SPAWN or TRAP_ACK PIPE (1-byte robust read) --- char buf[64]; int len = 0; @@ -5959,7 +6016,7 @@ static int ring_poll_main(int argc, char **argv) { } } buf[len] = '\0'; - + if (len > 0) { if (meta[i].type == 0) { char *colon = strchr(buf, ':'); @@ -5992,13 +6049,13 @@ static int ring_poll_main(int argc, char **argv) { free(pfds); free(meta); return EXECUTION_SUCCESS; } - } else { + } else { // --- DEATH PIPES (Scanner or Worker) --- bind_variable("POLL_EVENT", meta[i].type == 1 ? "SCAN_DEATH" : "WORKER_DEATH", 0); char arg_buf[32]; snprintf(arg_buf, sizeof(arg_buf), "%lld", (long long)meta[i].id); bind_variable("POLL_ARG1", arg_buf, 0); - + free(pfds); free(meta); return EXECUTION_SUCCESS; } @@ -6153,8 +6210,8 @@ static __thread struct forkrun_ctx tls_fctx; // ring_call: Zero-Tax C Plugin Callback Execution // --------------------------------------------------------- // NOTE FOR PLUGIN AUTHORS: -// The `argv` array and the string pointers it contains are backed by -// Thread-Local Storage. They are ONLY valid for the duration of the +// The `argv` array and the string pointers it contains are backed by +// Thread-Local Storage. They are ONLY valid for the duration of the // function call. Do not store these pointers across batches! static int ring_call_main(int argc, char **argv) { // Usage: ring_call @@ -6208,7 +6265,7 @@ static int ring_call_main(int argc, char **argv) { // 2. Tokenize the batch directly into tls_argv (starting at index 0) size_t batch_argc = 0; - int ret = do_tokenize(fd, length, delim, NULL, 0, &batch_argc); + int ret = do_tokenize(fd, length, tls_batch_offset, delim, NULL, 0, &batch_argc); if (ret != EXECUTION_SUCCESS) return ret; // 3. 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Z?J>&_@nhLFXVxQ1ewzbSmd2~~e*lh8s44&e literal 0 HcmV?d00001 diff --git a/frun.new.bash b/frun.new.bash new file mode 100755 index 00000000..9d60f69f --- /dev/null +++ b/frun.new.bash @@ -0,0 +1,1746 @@ +#!/usr/bin/bash + +if shopt -q extglob; then + extglob_was_set=true; +else + shopt -s extglob; +fi + +frun() { +## bash orchestrator function for forkrun, providing extremely fast shell streaming parallelization +# USAGE: . frun.bash && printf '%s\n' "${args[@]}" | frun [-flags] [--] parFunc ["${args0[@]}"] +# FLAGS: [-j ] [-l ][-b ] [-k|-u] [-s|-U] [-i|-I] [-d ] [-E] [-v] [-h] +# HELP: . frun.bash && frun --help +( + # 1. WRAPPER LOGIC (Current Shell) + [[ "${1}" == '__exec__' ]] || { + + # Check if already setup (and FD is valid), otherwise bootstrap + { ${FORKRUN_RING_ENABLED:-false} && (( ${FORKRUN_MEMFD_LOADABLES:-0} > 0 )); } || _forkrun_bootstrap_setup --fast + + # Generate list of loadables to enable in the new shell + (( ${#ring_funcs[@]} > 0 )) || ring_list 'ring_funcs' + printf -v ring_enable '%s ' "${ring_funcs[@]}" + + for nn in "${@##\-*}"; do + [[ ${nn} ]] && declare -F -- "$nn" &>/dev/null && ! [[ " ${FORKRUN_EXTRA_FUNCS} " == *" ${nn} "* ]] && FORKRUN_EXTRA_FUNCS+=" ${nn}" + done + FORKRUN_EXTRA_VARS+=' FORKRUN_EXTRA_FUNCS FORKRUN_EXTRA_VARS FORKRUN_EXTRA_SETUP' + + FORKRUN_FRUN_SRC+=$'\n'"$(declare -f -- frun ${FORKRUN_EXTRA_FUNCS:-} 2>/dev/null; declare -p -- ${FORKRUN_EXTRA_VARS} 2>/dev/null)" + [[ -n "${FORKRUN_EXTRA_SETUP}" ]] && FORKRUN_FRUN_SRC+=$'\n'"${FORKRUN_EXTRA_SETUP}" + + # EXEC into Clean Room + # /proc/self/fd/ is safer than $BASHPID in some namespace contexts + exec -c "${BASH:-bash}" --norc --noprofile -c 'enable -f "/proc/self/fd/'"${FORKRUN_MEMFD_LOADABLES}"'" '"${ring_enable}"' ring_list +export LC_ALL=C +set +m +shopt -s extglob +'"${FORKRUN_FRUN_SRC}"' +frun __exec__ "$@" +' -- "${@}" 0<&${fd00} 1>&${fd11} 2>&${fd22} + + # (Exec replaces process, so we never reach here) + } + # 2. WORKER LOGIC (Clean Shell) + shift 1 # Remove __exec__ + FORKRUN_ORIG_ARGS=("$@") + + # # # # # SETUP # # # # # + local cmdline_str ring_ack_str done_str delimiter_val pCode extglob_was_set worker_func_src nn N nWorkers0 arg fd0 fd1 fd2 numa_map_str parsed_numa_nodes_arg have_taskset_flag last_conflict numa_map_str exact_lines_val array_var resume_file order_mode unsafe_flag stdin_flag byte_mode_flag dry_run_flag checkpoint_file prefer_external_flag NORMAL_EXIT_FLAG c_plugin_arg + local -g fd_spawn_r fd_spawn_w fd_fallow_r fd_fallow_w fd_order_r fd_order_w ingress_memfd fd_write fd_scan nWorkers nWorkersMax tStart + local -gx LC_ALL + local -a fallow_args + local -ga fd_out P order_args ring_init_opts + + LC_ALL=C + set +m + + if shopt -q extglob; then + extglob_was_set=true; + else + shopt -s extglob; + extglob_was_set=false; + fi + + # --- HELPER: Expand units (IEC/IEEE prefixes) --- + _expand_unit() { + local val iec num p + val="${1,,}" + iec=false + [[ "${val#[+-]}" == '0' ]] && { REPLY="${val}"; return 0; } + [[ "${val}" == +* ]] && { iec=true; val="${val#+}"; } + num="${val//[^0-9]/}" + [[ $num ]] || if [[ ${val} ]]; then return 1; else REPLY=''; return 0; fi + { [[ "${num}" == "${val}" ]] || [[ -z ${num} ]]; } && { REPLY="${num}"; return 0; } + [[ "${val}" == *i* ]] && iec=true + p=0 + case "${val}" in + *k*) p=1 ;; *m*) p=2 ;; *g*) p=3 ;; *t*) p=4 ;; *p*) p=5 ;; *e*) p=6 ;; + esac + if ${iec}; then REPLY="${val[0]//[^-]/}$(( num << (10 * p) ))"; else REPLY="${val[0]//[^-]/}$(( num * (1000 ** p) ))"; fi + (( REPLY < -1 )) && { REPLY=$(( (1<<63) - 1 )); printf '\nWARNING: value expanded to larger than maximum int64. truncated to %s \n' "$REPLY" >&2; } + return 0 + } + + # --- HELPER: Parse Ranges (N, N:M, :M, N:) --- + _parse_count() { + local type val v1 v2 + case "$1" in + lines|bytes|workers) type="$1" ;; + *) return 1 ;; + esac + val="$2" + if [[ "$val" == *:* ]]; then + v1="${val%:*}"; v2="${val#*:}" + + _expand_unit "$v1"; ring_init_opts+=("--${type}0=${REPLY}"); + [[ $REPLY ]] && case "${type}" in + lines) byte_mode_flag=false ;; + bytes) byte_mode_flag=true ;; + esac + + _expand_unit "$v2"; ring_init_opts+=("--${type}-max=${REPLY}") + [[ $REPLY ]] && case "${type}" in + workers) nWorkersMax="${REPLY}" ;; + lines) byte_mode_flag=false ;; + esac + else + _expand_unit "$val"; ring_init_opts+=("--${type}=${REPLY}") + case "${type}" in + workers) [[ $REPLY ]] && nWorkersMax="${REPLY}" ;; + lines) byte_mode_flag=false ;; + bytes) byte_mode_flag=true ;; + esac + fi + return 0 + } + + # --- HELPER: Display HELP --- + _frun_displayHelp() { + case "$1" in + --usage|--help=usage) + cat <<'EOF' >&2 + +USAGE: . frun.bash && printf '%s\n' "${args[@]}" | frun [-flags] [--] parFunc ["${args0[@]}"] +FLAGS: [-j ] [-l ][-b ] [-k|-u] [-s|-U] [-i|-I] [-d ] [-E] [-v] [-h] +HELP: . frun.bash && frun --help + +EOF + ;; + *) + _frun_displayHelp "--usage" + cat <<'EOF' >&2 + +# # # # # FORKRUN V3 FLAGS # # # # # + +### DATA PASSING & DELIMITERS + : Pass arguments fully quoted via cmdline ("${A[@]}"). (no flag needed) + -U, --unsafe : Pass arguments unquoted via cmdline (${A[*]}). (WARNING: This flag forces Bash AST array expansion. Do NOT use this flag to speed up external binaries, as it disables the ultra-fast C-level vfork engine!) + -X, --external : Force external binary execution to enable the ultra-fast C-level vfork engine, which is FASTER than parallelizing the equivalent builtin command. If a command exists as both a builtin and a disk binary, this prefers the disk binary. (NOTE: If -U or -i or -I are used, the ultra-fast-path is disabled, and this flag has no effect). + -s, --stdin : Pass data to the worker via its stdin (instead of via cmdline arguments). + -b, --bytes : Byte mode. Split the stream into N-byte chunks instead of using delimiters (implies -s). Supports standard prefixes (e.g., -b 1M). + -z, --null : Use NULL (\0) as the record delimiter instead of newline. + -d, --delim : Use a custom single-character record delimiter. + +### OUTPUT MODES + --buffered : (DEFAULT) Buffered / "atomic fan-in" mode. Output is stored in a memfd and printed once the whole batch finishes. + -k, --ordered : Ordered mode. Same as buffered, but output is printed strictly in input-batch order. + -u, --realtime : Unbuffered / realtime mode. Workers output directly to stdout. (Can cause kernel lock contention on massive streams). + -o, --order : Explicitly set the mode (buffered, ordered, realtime). + +### WORKER & BATCH SCALING (Dynamic Ranges) + *Syntax note: Options accepting : allow you to define the starting value and the upper bound for the dynamic PID controller. Setting and to 0 or -1 has special meaning. Examples: 1:0 (DEFAULT) (start at 1, scale to default max) | 0:-1 (start at default max, scale to maximum allowed) | 4:16 (start at 4, scale to max of 16).* + + -j, -P, --workers : Set the number of concurrent workers. Supports : (e.g., -j 4:32). Default max is the number of logical cores. + -l, --lines : Set the batch size (lines per worker). Supports : (e.g., -l 10:10000). Default max is 4096. + -L, --exact-lines : Force exactly N lines per batch. (Warning: Disables NUMA topological stealing to guarantee exact counts). + -t, --timeout : Set the maximum wait time (in microseconds) for a partial batch before flushing early. + +### STRING SUBSTITUTION + -i, --insert : Replace {} in the command string with the inputs passed on stdin. + -I, --insert-id : Replace {ID} in the command string with [{NODE_NUM}.]{WORKER_NUM}.{BATCH_NUM}. {ID} is unique per batch, and can be used to redirect output per batch. + +### LIMITS & TOPOLOGY + -n, --limit : Stop processing after exactly N records have been claimed. + --nodes, --numa : Control NUMA topology mapping. Nodes that do not exist will be skipped (excluding for @N). + auto (default): Autodetect all physical online nodes. + @N: Oversubscribe / force N logical nodes. + 0,1: Explicitly bind to physical NUMA nodes 0 and 1. + 0:3: Explicitly bind to physical NUMA nodes 0 and 1 and 2 and 3. + -N, --dry-run : Dry run. Print the generated command strings instead of executing them. + -v, --verbose : Increase verbosity (prints timing and flag summaries to stderr). Implies --stats. + +v, --no-verbose : Decrease verbosity. Disables --stats. + -V, --version : Prints forkrun version number + --stats : Prints NUMA statistics to stderr (currently ignored for UMA) + +### ERROR HANDLING & RETRIES + -E, --retry-nonzero-exit : Activate auto-retry machinery for commands returning non-zero exit codes. When active, `|| exit $?` is appended to the parallelized command, meaning any non-zero return triggers a worker kill and batch retry. + *Note on subshells*: When parallelizing functions that spawn subshells without -E active, + failures must be manually guarded to return 200 to trigger the retry machinery (along with + 137 SIGKILL and 139 SIGSEGV). To protect the entire subshell, use the following pattern: + ff() { + # ... + ( + # all subshell cmds + true # <--- ADD THIS AT THE VERY END OF THE SUBSHELL + ) || return 200 + # ... + } + +### CHECKPOINT & RESUME + --resume : Resume a previously aborted pipeline using the specified checkpoint file. + - Buffered/Ordered modes: Provides "Exactly-Once" semantics. Ensure you truncate your output file to the byte count specified in the crash message before resuming. + - Realtime (-u) mode: Provides "At-Least-Once" semantics. Resuming may result in a few duplicate lines at the failure boundary. + --checkpoint-file : Specify a custom filename for the checkpoint file written on failure. (Default: .forkrun_resume) + +### UNSETTING FLAGS + +U, +s, +N, +i, +I, +E, +X, +v, --no-stats : disables the corresponding flag listed above, restoring default behavior. If both +flag and -flag are used, the last one passed is used. + +### ENVIRONMENT VARS + FORKRUN_RETRY_LIMIT : Controls how many times a batch will be retried before it is declared poisoned. 0 means declared poisoned after the 1st failure. A negative value means it will never be declared poisoned (and could retry indefinitely). Default is 3. + FORKRUN_EXTRA_FUNCS : Use this to specify required sub-functions to pass into frun's environment. + EXAMPLE: `hh() { echo "$@"; }; gg() { hh "$@"; }; ff() { gg "$@"; };`. If you call `frun ff /dev/null)" + resume_flag=true + + # If the user only provided the resume file (no extra args), inject the original ones + if (( $# == 1 )) && (( ${#FORKRUN_ORIG_ARGS[@]} > 0 )); then + + # Set positional parameters: keep resume_file at $1 so the bottom + # 'shift' safely drops it, then append the original arguments. + set -- "" "${FORKRUN_ORIG_ARGS[@]}" + + # Resurrect the bash functions into the current shell environment + [[ -n "${FORKRUN_EXTRA_SETUP:-}" ]] && eval "${FORKRUN_EXTRA_SETUP}" + fi + + # We intentionally do NOT call 'continue' here! + # This allows the loop to hit the 'shift' at the bottom of the case statement, + # which will drop $1 (the resume_file) and smoothly begin parsing the + # newly injected FORKRUN_ORIG_ARGS on the next iteration. + else + echo "forkrun [ERROR]: Resume file '$resume_file' not found." >&2 + return 1 + fi ;; + + # --- LIMIT (-n 100) --- + @(-n|--limit)?(?([= $'\t'])+([0-9+-]))) + arg="${1##@(-n|--limit)?([= $'\t'])}"; + [[ ${arg}${2//+([0-9+-])/} ]] || { shift; arg="$1"; } + [[ ${arg} ]] && _expand_unit "${arg}" && ring_init_opts+=('--limit='"$REPLY") ;; + + # --- EXACT LINES (-L 100) --- + @(-L|--exact-lines|--LINES|--EXACT-LINES)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) + arg="${1##@(-L|--exact-lines|--LINES|--EXACT-LINES)?([= $'\t'])}"; + [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } + [[ ${arg} ]] && { exact_lines_val="${arg}"; last_conflict="exact_lines"; } ;; + + # --- LINES / BATCH (-l 1k or -l 100:1k) --- + @(-l|--lines|--batchsize)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) + arg="${1##@(-l|--lines|--batchsize)?([= $'\t'])}"; + [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } + [[ ${arg} ]] && _parse_count "lines" "${arg}" ;; + + # --- BYTES (-b 1M) --- + @(-b|--bytes)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) + arg="${1##@(-b|--bytes)?([= $'\t'])}"; + [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } + _parse_count "bytes" "${arg:-}" ;; + + # --- WORKERS (-j 4 or -j 1:8) --- + @(-j|-P|--workers)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) + arg="${1##@(-j|-P|--workers)?([= $'\t'])}"; + [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } + [[ ${arg} ]] && _parse_count "workers" "${arg}" ;; + + # --- TIMEOUT (-t 5000) --- + @(-t|--timeout)?(?([= $'\t'])+([0-9.+-]))) + arg="${1##@(-t|--timeout)?([= $'\t'])}"; + [[ ${arg}${2//+([0-9.+-])/} ]] || { shift; arg="$1"; } + [[ ${arg} ]] && _expand_unit "${arg}" && ring_init_opts+=('--timeout='"${REPLY}") ;; + + # --- NUMA NODES (--nodes auto) --- + @(--nodes|--numa)?(?([= $'\t'])*)) + arg="${1##@(--nodes|--numa)?([= $'\t'])}"; + [[ ${arg} ]] || { shift; arg="$1"; } + [[ ${arg} ]] && { parsed_numa_nodes_arg="${arg}"; last_conflict="nodes"; } ;; + + # --- ORDER (-o buffered) --- + @(-o|--order)?(?([= $'\t'])@(realtime|unbuffered|buffered|atomic|order?(ed)))) + arg="${1##@(-o|--order)?([= $'\t'])}"; + [[ ${arg}${2//@(realtime|unbuffered|buffered|atomic|order?(ed))/} ]] || { shift; arg="$1"; } + case "${arg}" in + realtime|unbuffered) order_mode='realtime' ;; + buffered|atomic) order_mode='buffered' ;; + order|ordered|'') order_mode='ordered' ;; + *) order_mode='buffered' ;; + esac ;; + + # --- DELIMITER (-d x) --- + @(-d|--delim|--delimiter)?(?([= $'\t'])*)) + arg="${1##@(-d|--delim|--delimiter)?([= $'\t'])}"; + if [[ -z "${arg}" && "$1" == @(-d|--delim|--delimiter) ]]; then + shift; arg="$1"; + fi + delimiter_val="${arg:0:1}" ;; + + # help system + -h|-\?|--help|--help=*|--usage) _frun_displayHelp "$1"; return 0 ;; + + -V|--version|--VERSION) echo 'forkrun v3.2.1'; return 0 ;; + + --) shift; break ;; + + *) break ;; + esac + shift + done + unset arg + # --- AST MANIPULATION FOR BASH FUNCTIONS --- + declare -F -- "$1" &>/dev/null 2>&1 && is_func_flag=true + if [[ -n "$1" ]] && ${is_func_flag}; then + local func_def body body_start body_trimmed test_body + func_def="$(declare -f -- "$1")" + + # 1. Extract the contents inside the global { ... } + body="${func_def#*\{}" + body="${body%\}}" + + # Trim leading and trailing whitespace + body_trimmed="${body##+([[:space:]])}" + body_trimmed="${body_trimmed%%+([[:space:]])}" + + # 2. Check if it visually starts and ends with parentheses + if [[ "$body_trimmed" == \(*\) ]]; then + # Strip the very first '(' and the very last ')' + test_body="${body_trimmed#\(}" + test_body="${test_body%\)}" + + # 3. THE GENIUS CHECK: Ask the Bash parser if this is valid! + # We run this in a subshell to keep the environment perfectly clean. + # Explicit newlines prevent trailing comments from breaking the brace. + if ( "${BASH:-bash}" -O extglob -n -c "function _frun_syntax_check() {"$'\n'"${test_body}"$'\n'"}" ) >/dev/null 2>&1; then + # It is a verified global subshell! + # Strip the last ')' and inject 'true' safely inside it. + retry_nonzero_exit_flag=true + body_start="${body_trimmed%?}" + eval "${func_def%%\{*}"'{'$'\n'"${body_start}"$'\n''true'$'\n'')'$'\n''}' + fi + fi + + unset func_def body body_start body_trimmed test_body + fi + + ${extglob_was_set} || shopt -u extglob + + if ${verbose_flag}; then + tStart="${EPOCHREALTIME//./}" +toc() { + printf '\n%s finished at +%s us\n' "$*" "$(( ${EPOCHREALTIME//./} - tStart ))" >&$fd2 +} + else +toc() { :; } + fi + + : "${nWorkersMax:=$(nproc)}" + + # Resolve Default Modes + [[ -z ${stdin_flag} ]] && { + if ${byte_mode_flag:-false}; then + stdin_flag=true + else + stdin_flag=false + fi + } + + if ${stdin_flag:-false}; then + unsafe_flag=false + ring_init_opts+=('--stdin') + elif ${byte_mode_flag:-false}; then + : "${stdin_flag:=true}" + ring_init_opts+=('--stdin') + elif ${unsafe_flag:-false}; then + stdin_flag=false + fi + + ${byte_mode_flag:-false} && ring_init_opts+=('--lines=x') + + ring_init_opts+=("--delim=${delimiter_val}") + + [[ "${order_mode}" == "realtime" ]] || ring_init_opts+=('--out=fd_out') + + # --- NUMA Node Discovery and Topology Mapping --- + : "${parsed_numa_nodes_arg:=auto}" + + _forkrun_build_numa_map() { + local req c + local -a online map parts req_list + req="$1" + + # NEW: Explicit Global UMA (No Pinning) + if [[ "$req" == "@0" || "$req" == "0" || "$req" == "uma" || "$req" == "none" ]]; then + export FORKRUN_NUM_NODES=1 + numa_map_str="" + return 0 + fi + + if [[ -r /sys/devices/system/node/online ]]; then + local raw; read -r raw < /sys/devices/system/node/online + if [[ -n "$raw" ]]; then + IFS=',' read -ra parts <<< "$raw" + for p in "${parts[@]}"; do + if [[ "$p" == *-* ]]; then + for (( i=${p%%-*}; i<=${p##*-}; i++ )); do online+=("$i"); done + else + online+=("$p") + fi + done + fi + fi + (( ${#online[@]} == 0 )) && online=(0) + + map=() + if [[ "$req" == "auto" ]]; then + map=("${online[@]}") + elif [[ "$req" == @* ]]; then + # Oversubscribe / Forced Count mode: --nodes=@N + c="${req#@}" + for (( i=0; i 1 )); then + local orig_pos file_size + if ring_lseek 0 0 SEEK_CUR orig_pos; then + if ring_lseek 0 0 SEEK_END file_size; then + local remaining_bytes=$(( file_size - orig_pos )) + if (( remaining_bytes > 0 && remaining_bytes < FORKRUN_NUM_NODES * 8192 )); then + parsed_numa_nodes_arg="1" + _forkrun_build_numa_map "1" + fi + fi + ring_lseek 0 "${orig_pos}" SEEK_SET orig_pos + fi + fi + + # --- Feature 2: -L vs NUMA Conflict Resolution --- + if [[ -n "${exact_lines_val:-}" ]] && (( FORKRUN_NUM_NODES > 1 )); then + if [[ "$last_conflict" == "exact_lines" ]]; then + printf '\nforkrun [WARNING]: To facilitate using exactly %s arguments per batch, forkrun will run in UMA mode. NUMA optimizations prevent -L from working properly, and will be disabled.\n\n' "${exact_lines_val}" >&2 + # Force UMA mode by re-building the map with exactly 1 node + _forkrun_build_numa_map "1" + else + printf '\nforkrun [WARNING]: forkrun cannot guarantee exactly %s lines per batch in NUMA mode. The -L option has been downgraded to -l, which guarantees a maximum of %s lines per batch. If you need exactly %s lines per batch, remove the --nodes option from the invocation.\n\n' "${exact_lines_val}" "${exact_lines_val}" "${exact_lines_val}" >&2 + # Downgrade to -l (clear exact lines flag so it just parses normally below) + _parse_count "lines" "${exact_lines_val}" + exact_lines_val="" + fi + fi + + # If exact_lines_val survived (either it was UMA, or we forced UMA), apply it + if [[ -n "${exact_lines_val:-}" ]]; then + _parse_count "lines" "${exact_lines_val}" + ring_init_opts+=("--exact-lines") + fi + + if [[ -n "$numa_map_str" ]]; then + ring_init_opts+=("--numa-map=$numa_map_str") + fi + + # Initialize Ring + ring_init "${ring_init_opts[@]}" + : "${FORKRUN_NUM_NODES:=1}" # Fallback safety + + # Create Data Memfd + ring_memfd_create ingress_memfd + + # NEW: Apply Checkpoint if Resuming + ${resume_flag} && ring_set_resume "$FORKRUN_RESUME_HORIZON" "${FORKRUN_RESUME_JAGGED[@]}" + + # # # # # MAIN # # # # # + { + trap ' + + status=${_ret_val:-$?} + if ! ${NORMAL_EXIT_FLAG:-false}; then + echo "forkrun [FATAL]: Pipeline aborted. Generating checkpoint..." >&2 + ${NORMAL_EXIT_FLAG:-true} || ring_abort + + # ALWAYS write the resume file! + ring_dump_resume > "'"${checkpoint_file}"'" + for nn in ${FORKRUN_EXTRA_FUNCS}; do + declare -F -- "${nn}" &>/dev/null && ! [[ "${FORKRUN_EXTRA_SETUP}" == *$'"'"'\n'"'"'"${nn}"$'"'"' () \n{'"'"'*'"'"'}'"'"'* ]] && FORKRUN_EXTRA_SETUP+=" +$(declare -f -- "${nn}")" + done + declare -p -- FORKRUN_ORIG_ARGS ${FORKRUN_RETRY_LIMIT:+${FORKRUN_RETRY_LIMIT}} ${FORKRUN_EXTRA_VARS} 2>/dev/null >> "'"${checkpoint_file}"'" + + if [[ "${order_mode}" != "realtime" ]]; then + local safe_bytes="$(grep -E '"'"'^FORKRUN_RESUME_STDOUT_BYTES='"'"' "${checkpoint_file}")" + safe_bytes="${safe_bytes#*=}" + echo "forkrun: To resume safely, truncate your output file to exactly ${safe_bytes} bytes," >&2 + echo " then re-run your exact command with: --resume '"${checkpoint_file}"'" >&2 + else + echo "forkrun: Warning - Realtime mode (-u) checkpoint generated." >&2 + echo " Resuming will result in some duplicate lines at the failure boundary (At-Least-Once semantics)." >&2 + echo " Re-run your exact command with: --resume '"${checkpoint_file}"'" >&2 + fi + fi + # Clean up memory only AFTER the trap is done with it! + ring_destroy 2>/dev/null + return $status + ' EXIT INT + ring_pipe fd_spawn_r fd_spawn_w + + # --- 1. RING FALLOW --- + ring_pipe fd_fallow_r fd_fallow_w + + # --- 2 & 3. THE PRODUCER PLUMBING --- + declare -a fd_scan_death_r fd_scan_death_w SCANNER_P + ring_pipe fd_trap_ack_r fd_trap_ack_w + + if (( FORKRUN_NUM_NODES > 1 )); then + # NUMA TOPOLOGICAL PIPELINE + ordered_flag=0 + [[ "${order_mode}" == "ordered" ]] && ordered_flag=1 + + ( exec {fd_trap_ack_w}>&-; ring_numa_ingest ${fd0} ${fd_write} $FORKRUN_NUM_NODES $ordered_flag ) & + + for (( i=0; i&-; ring_indexer_numa ${fd_scan} $i ) & + done + + for (( i=0; i&- {fd_trap_ack_w}>&- + ring_numa_scanner ${fd_scan} $i $fd_spawn_w $FORKRUN_NUM_NODES + ) & + SCANNER_P[$i]=$! + exec {fd_scan_death_w[$i]}>&- + done + + else + # LEGACY FLAT PIPELINE + ( exec {fd_trap_ack_w}>&-; ring_copy ${fd_write} ${fd0}; ring_signal ) & + ring_pipe fd_scan_death_r[0] fd_scan_death_w[0] + ( + exec {fd_spawn_r}<&- {fd_trap_ack_w}>&- + ring_scanner ${fd_scan} ${fd_spawn_w} + ) & + SCANNER_P[0]=$! + exec {fd_scan_death_w[0]}>&- + fi + + exec {fd_spawn_w}>&- + + ( + exec {fd_fallow_w}>&- {fd_trap_ack_w}>&- + fallow_args=( "${fd_fallow_r}" "${fd_write}" ) + if (( FORKRUN_NUM_NODES > 1 )); then + ring_fallow_phys "${fallow_args[@]}" + else + ring_fallow "${fallow_args[@]}" + fi + ) & + exec {fd_fallow_r}<&- + + # --- 4. RING ORDER --- + [[ "${order_mode}" == "realtime" ]] || { + ring_pipe fd_order_r fd_order_w + ( + exec {fd_order_w}>&- {fd_trap_ack_w}>&- + + order_args=( "${fd_order_r}" 'memfd' ) + [[ "${order_mode}" == "buffered" ]] && order_args+=( "unordered" ) + (( FORKRUN_NUM_NODES > 1 )) && order_args+=( "numa" ) + + ring_order "${order_args[@]}" >&${fd1} + ) & + exec {fd_order_r}<&- + export FD_ORDER_PIPE=$fd_order_w + } + + # --- WORKER DEFINITION --- + printf -v cmdline_str '%q ' "$@" + + # 1. Replace {ID} with the Worker ID, NUMA Node ID, and Worker Batch Num + if ${insert_id_flag:-false}; then + cmdline_str="${cmdline_str//\\\{ID\\\}/\{\${RING_NODE_ID:+\$\{RING_NODE_ID\}.\}\$\{ID\}.\$\{W_BATCH\}\}}" + fi + + ${dry_run_flag:-false} && printf -v cmdline_str 'echo %q' "${cmdline_str}" + + ring_ack_str="ring_ack $fd_fallow_w" + + # Determine if the target command is safe for direct posix_spawn + local cmd_type + if ${prefer_external_flag:-false}; then + cmd_type=$(type -Pt "$1" 2>/dev/null) + else + cmd_type=$(type -t "$1" 2>/dev/null) + fi + local use_ultra_fast_path=false + + # Only use the fast path if it's an external file, safe mode, and no {} insertions + if [[ "$cmd_type" == "file" ]] && ! ${unsafe_flag:-false} && ! ${insert_args_flag:-false}; then + # Resolve absolute path (e.g., "grep" -> "/usr/bin/grep") + local cmd_path=$(type -P "$1" 2>/dev/null) + + if [[ -n "$cmd_path" ]]; then + # Check if it's a compiled binary or has a shebang + if ring_is_spawnable "$cmd_path"; then + use_ultra_fast_path=true + fi + fi + fi + + if [[ -n "${c_plugin_arg:-}" ]]; then + # Ensure the user actually passed a colon! + if [[ "$c_plugin_arg" != *:* ]]; then + echo "forkrun [FATAL]: -C requires format 'path/to/plugin.so:function_name'" >&2 + return 1 + fi + + # C PLUGIN PAYLOAD (ULTRA-FASTEST PATH) + local plugin_so="${c_plugin_arg%:*}" + local plugin_fn="${c_plugin_arg#*:}" + + type -P realpath &>/dev/null && plugin_so="$(realpath "$plugin_so")" + + # --- JIT C-COMPILER LOGIC (With Fileless Execution) --- + local plugin_c="${plugin_so%.so}.c" + + # Recompile if .so is missing, or if .c is newer than .so + if [[ -f "$plugin_c" && ( ! -f "$plugin_so" || "$plugin_c" -nt "$plugin_so" ) ]]; then + if type -P gcc >/dev/null; then + local target_so="$plugin_so" + local use_memfd=false + + # Check if we have write access to the directory + if [[ ! -w "${plugin_so%/*}/" ]]; then + use_memfd=true + fi + + if $use_memfd; then + ${verbose_flag} && echo "forkrun [INFO]: Read-only filesystem detected. Compiling $plugin_c to memfd..." >&2 + ring_memfd_create plugin_memfd + target_so="/proc/self/fd/$plugin_memfd" + else + ${verbose_flag} && echo "forkrun [INFO]: Auto-compiling $plugin_c -> $plugin_so" >&2 + fi + + # Compile directly to the target (Disk or RAM) + gcc -O3 -shared -fPIC -march=native "$plugin_c" -o "$target_so" || { + echo "forkrun [FATAL]: Auto-compilation of $plugin_c failed." >&2 + return 1 + } + + if $use_memfd; then + # Seal the memfd to prevent tampering, and override the plugin_so path + ring_seal "$plugin_memfd" + plugin_so="$target_so" + fi + else + echo "forkrun [FATAL]: 'gcc' is not installed to compile $plugin_c." >&2 + return 1 + fi + fi + + # Sanity check: Ensure we actually have a target to execute before spawning workers + if [[ ! -f "$plugin_so" ]]; then + echo "forkrun [FATAL]: Plugin '$plugin_so' not found or could not be compiled." >&2 + return 1 + fi + + if [[ ${delimiter_val} ]]; then + printf -v delimiter_str '%q' "${delimiter_val}" + else + delimiter_str="''" + fi + + pCode=' + ring_call $fd_read $REPLY '"${delimiter_str} ${plugin_so@Q} ${plugin_fn@Q}" + + elif ${stdin_flag}; then + # STDIN PAYLOAD + if $use_ultra_fast_path; then + # ALL-IN-C ZERO-COPY PIPELINE + pCode='ring_exec_splice $fd_read $REPLY '"$cmdline_str" + else + # STANDARD BASH PIPE PIPELINE + : "${RING_BYTES_MAX:=1000000000}" "${RING_PIPE_CAPACITY:=65536}" + + local exec_cmd_str="$cmdline_str" + pCode=' + pipe_open_flag=0 + if (( REPLY <= RING_PIPE_CAPACITY - 4096 )); then + ring_pipe pr pw + pipe_open_flag=1 + else + RING_PIPE_CAPACITY_CUR=0 + fi + + # opportunistically probe the kernels granted capacity + if (( pipe_open_flag && REPLY <= RING_PIPE_CAPACITY_CUR - 4096 )); then + # FAST PATH (Synchronous) + # Note: ring_splice "close" closes $pw internally. We only close $pr. + ring_splice $fd_read $pw "-" $REPLY "close" 2>/dev/null || exec {pw}>&- + '"$exec_cmd_str"' <&$pr' + if ${retry_nonzero_exit_flag}; then + pCode+=' || exit $?' + elif ${is_func_flag}; then + pCode+=' + ret=$? + (( ret == 137 || ret == 139 || ret == 200 )) && exit $ret' + fi + pCode+=' + exec {pr}<&- + else + # SLOW PATH (Asynchronous) + # Close both FDs so they do not leak into the pipeline + (( pipe_open_flag )) && exec {pr}<&- {pw}>&- + ( ring_splice $fd_read 1 "-" $REPLY "close" ) | ( '"$exec_cmd_str"' )' + if ${retry_nonzero_exit_flag}; then + pCode+=' || exit $?' + elif ${is_func_flag}; then + pCode+=' + ret=$? + (( ret == 137 || ret == 139 || ret == 200 )) && exit $ret' + fi + pCode+=' + fi' + fi + + elif ${byte_mode_flag}; then + # BYTE MODE WITHOUT PASS-BY-STDIN + # BYTE ARGS PAYLOAD + array_var='"${A}"' + if ${insert_args_flag:-false}; then + cmdline_str="${cmdline_str//\\\{\\\}/$array_var}" + else + cmdline_str+=" $array_var" + fi + + if $use_ultra_fast_path; then + # Length 0 bypasses do_tokenize and acts as pure vfork wrapper + pCode='ring_exec 0 0 '\'''\'' '"$cmdline_str" + else + pCode=' + ring_lseek $fd_read - SEEK_SET _dummy + read -r -u $fd_read -N $REPLY A + '"$cmdline_str" + fi + + else + # LINE ARGS PAYLOAD (Default) + + if $use_ultra_fast_path; then + # ULTRA-FAST PATH: Bypass Bash AST entirely! + if [[ ${delimiter_val} ]]; then + printf -v delimiter_str '%q' "${delimiter_val}" + else + delimiter_str="''" + fi + + # $cmdline_str already contains the quoted command and fixed args + pCode=' + ring_exec $fd_read $REPLY '"${delimiter_str}"' '"$cmdline_str" + else + # STANDARD FAST PATH: Mapfile replacement for Shell Functions & Builtins + array_var='"${A[@]}"' + ${unsafe_flag} && array_var='${A[*]}' + + if ${insert_args_flag:-false}; then + cmdline_str="${cmdline_str//\\\{\\\}/$array_var}" + else + cmdline_str+=" $array_var" + fi + + if ${unsafe_flag}; then + cmdline_str="IFS=' ' ${cmdline_str}" + fi + + if [[ ${delimiter_val} ]]; then + printf -v delimiter_str '%q' "${delimiter_val}" + else + delimiter_str="''" + fi + + pCode=' + ring_map $fd_read $REPLY A '"${delimiter_str}"' + '"$cmdline_str" + fi + fi + + [[ "${order_mode}" == "realtime" ]] || { + pCode+=' >&${fd_out[$RING_WID]}' + ring_ack_str+=' ${fd_out[$RING_WID]}' + } + + ${stdin_flag} || { + if ${retry_nonzero_exit_flag}; then + pCode+=' || exit $?' + elif ${is_func_flag}; then + pCode+=' + ret=$? + (( ret == 137 || ret == 139 || ret == 200 )) && exit $ret' + fi + } + + worker_func_src='spawn_worker() { +( + LC_ALL=C + set +m + export RING_NODE_ID="$2" + export RING_WID="$3" + export FD_TRAP_ACK_W="$4" + + _ring_registered=false + + trap '"'"' + status=$? + ${_ring_registered} && { ring_worker dec; ring_cleanup_waiter; } + + if (( status != 0 && ${FRUN_CLAIM_BYTES:-0} > 0 )); then + (( RING_NUM_KILLS++ ))' + [[ "$order_mode" != "realtime" ]] && worker_func_src+=' + [[ -n "${fd_out[$RING_WID]:-}" ]] && ring_revert_output "${fd_out[$RING_WID]}" + ' + worker_func_src+=' + ring_escrow_put "$RING_NODE_ID" "-" "-" "$RING_NUM_KILLS" + fi + + # Notify parent that the trap successfully fired + if (( status != 0 )); then + echo "$RING_WID" >&"${FD_TRAP_ACK_W}" 2>/dev/null + fi + exit $status + '"'"' EXIT + + trap '"'"'ring_abort + kill -INT '"${BASHPID}'"' INT + + { + ID="$1" # ID is passed purely for user payload compatibility/insertion + RING_NUM_KILLS=0 + RING_POISONED=0 + FRUN_CLAIM_BYTES=0 + REPLY=0 + ' + [[ "$order_mode" != "realtime" ]] && worker_func_src+=' + # Initialize the output tracking for this specific worker slot + [[ -n "${fd_out[$RING_WID]:-}" ]] && ring_ack_init "${fd_out[$RING_WID]}" + ' + ${insert_id_flag:-false} && worker_func_src+='W_BATCH=0 + ' + worker_func_src+='shift 4 + ring_worker inc + _ring_registered=true + while ring_claim FRUN_CLAIM_BYTES; do + if [[ "${RING_POISONED}" == "1" ]]; then + echo "forkrun [WARN]: Skipping poisoned batch $RING_BATCH_IDX (killed ${RING_NUM_KILLS} times)." >&2 + echo "P:${RING_BATCH_IDX}:${RING_NUM_KILLS}" >&"${FD_TRAP_ACK_W}" 2>/dev/null + else + REPLY=$FRUN_CLAIM_BYTES + if [[ "$REPLY" != "0" ]]; then + ' + ${insert_id_flag:-false} && worker_func_src+='((W_BATCH++)) + ' + worker_func_src+="${pCode}"' + fi + fi + '"${ring_ack_str}"' || break + + # Reset variables natively in Bash so C does not have to allocate them + RING_POISONED=0 + RING_NUM_KILLS=0 + FRUN_CLAIM_BYTES=0 + REPLY=0 + done + } {fd_read}<"/proc/self/fd/'"${ingress_memfd}"'" 1>&${fd1} 2>&${fd2} +) & +P[$3]=$! +W_NODE[$3]=$2 +}' + + eval "${worker_func_src}" + + # --- SPAWN LOOP REACTOR --- + nWorkers=0 + local -a node_workers W_NODE fd_worker_r fd_worker_w P wID_free + + local -A trap_ack_pending + local _poll_timer_cmd=0 + local _timer_armed=false + local _ret_val=0 + local -a POISONED_BATCHES=() + + for ((i=0; i 0 )); then + echo "forkrun [FATAL]: Worker(s) [ ${!trap_ack_pending[@]} ] exited non-zero and EXIT trap did not confirm recovery within 3s grace period. Aborting." >&2 + ring_abort + NORMAL_EXIT_FLAG=false + _ret_val=2 + fi + ;; + TRAP_ACK) + # NEW: Catch Poisoned Batch Signals + if [[ "$POLL_ARG1" == P:* ]]; then + local p_data="${POLL_ARG1#P:}" + POISONED_BATCHES+=("Index ${p_data%:*} (failed ${p_data##*:} times)") + continue + fi + + wID=$POLL_ARG1 + (( trap_ack_pending[$wID]-- )) + + # If it balanced out to 0 (DEATH arrived first), clean it up + if (( trap_ack_pending[$wID] == 0 )); then + unset 'trap_ack_pending[$wID]' + fi + + if (( ${#trap_ack_pending[@]} == 0 )); then + _poll_timer_cmd=-1 # Cancel timer cleanly + _timer_armed=false + fi + ;; + SPAWN) + spawn_count=$POLL_ARG1 + node_idx=$POLL_ARG2 + + target=$(( node_workers[node_idx] + spawn_count )) + (( target > node_worker_max )) && target=$node_worker_max + + for (( ; node_workers[node_idx] < target; node_workers[node_idx]++ )); do + for wID in "${!wID_free[@]}"; do break; done + unset 'wID_free[$wID]' + + ring_pipe fd_worker_r[$wID] fd_worker_w[$wID] + spawn_worker "$wID" "$node_idx" "$wID" "${fd_trap_ack_w}" + exec {fd_worker_w[$wID]}>&- + ((nWorkers++)) + done + ;; + WORKER_DEATH) + wID=$POLL_ARG1 + wait "${P[$wID]}" 2>/dev/null + status=$? + + exec {fd_worker_r[$wID]}<&- + unset 'fd_worker_r[$wID]' 'fd_worker_w[$wID]' 'P[$wID]' + + node_idx=${W_NODE[$wID]:-0} + unset 'W_NODE[$wID]' + + (( node_workers[node_idx]-- )) + + if (( status != 0 )); then + (( trap_ack_pending[$wID]++ )) + + if (( trap_ack_pending[$wID] == 0 )); then + # TRAP_ACK already arrived! Clean up safely. + unset 'trap_ack_pending[$wID]' + elif (( trap_ack_pending[$wID] > 0 )); then + # Death arrived before TRAP_ACK. Arm the 3-second deadline. + if ! $_timer_armed; then + _poll_timer_cmd=3000 + _timer_armed=true + echo "forkrun [WARN]: Worker $wID (node ${node_idx}) exited with status $status. Waiting up to 3s for EXIT trap confirmation." >&2 + fi + fi + + # Unconditionally respawn replacement worker + ring_pipe fd_worker_r[$wID] fd_worker_w[$wID] + spawn_worker "$wID" "$node_idx" "$wID" "${fd_trap_ack_w}" + exec {fd_worker_w[$wID]}>&- + ((nWorkers++)) + (( node_workers[node_idx]++ )) + else + wID_free[$wID]='' + fi + ;; + SCAN_DEATH) + sID=$POLL_ARG1 + wait "${SCANNER_P[$sID]}" 2>/dev/null + status=$? + + if (( status != 0 )); then + echo "forkrun [FATAL]: Scanner $sID exited with error status $status. Aborting to prevent data loss." >&2 + ring_abort + NORMAL_EXIT_FLAG=false + _ret_val=1 + fi + + exec {fd_scan_death_r[$sID]}<&- + unset 'fd_scan_death_r[$sID]' 'SCANNER_P[$sID]' + ;; + EOF) + fd_spawn_arg="-1" + ;; + esac + done + : "${NORMAL_EXIT_FLAG:=true}" + + ${verbose_flag} && printf '\nSPAWNED %s workers\n' "${nWorkers}" >&2 + + # --- SHUTDOWN --- + exec {fd_spawn_r}<&- {fd_fallow_w}>&- {fd_trap_ack_r}<&- {fd_trap_ack_w}>&- + [[ "${order_mode}" == "realtime" ]] || exec {fd_order_w}>&- + + wait + + { ${stats_flag} || ${verbose_flag}; } && (( FORKRUN_NUM_NODES > 1 )) && ring_numa_stats + + if (( ${#POISONED_BATCHES[@]} > 0 )); then + echo -e "\n=================================================================" >&2 + echo "forkrun [ERROR]: POISONED BATCH SUMMARY" >&2 + echo "=================================================================" >&2 + echo "The pipeline completed, but ${#POISONED_BATCHES[@]} batch(es) failed repeatedly" >&2 + echo "and were permanently skipped:" >&2 + for b in "${POISONED_BATCHES[@]}"; do + echo " - Batch $b" >&2 + done + echo "=================================================================" >&2 + + # If we were going to exit 0, change it to exit 3 to signal data loss + (( _ret_val == 0 )) && _ret_val=3 + fi + + exec {fd_write}>&- {fd_scan}>&- {ingress_memfd}>&- + + } {fd_write}>"/proc/${BASHPID}/fd/${ingress_memfd}" {fd_scan}<"/proc/${BASHPID}/fd/${ingress_memfd}" {fd0}<&0 {fd1}>&1 {fd2}>&2 + return $_ret_val + ) {fd00}<&0 {fd11}>&1 {fd22}>&2 +} + +# ============================================================================== +# BASH AUTO-COMPLETION FOR FRUN +# ============================================================================== +_frun_complete() { + local cur prev opts + COMPREPLY=() + cur="${COMP_WORDS[COMP_CWORD]}" + prev="${COMP_WORDS[COMP_CWORD-1]}" + + # V3 Supported Flags + opts="-k --keep-order --ordered -u --unbuffered --realtime --buffered --atomic \ + -U --unsafe +U --safe -s --stdin +s --no-stdin -v --verbose +v --no-verbose \ + -z --null -N --dry-run -i --insert -I --insert-id -n --limit -L --exact-lines \ + -E --retry-nonzero-exit +E --no-retry-nonzero-exit \ + -l --lines --batchsize -b --bytes -j -P --workers -t --timeout --nodes --numa \ + -o --order -d --delim --delimiter -h --help --usage" + + # If the user is currently typing a flag + if [[ ${cur} == -* ]] ; then + COMPREPLY=( $(compgen -W "${opts}" -- "${cur}") ) + return 0 + fi + + # If the user is typing the command to parallelize + if [[ ${prev} == frun || ${prev} == -* ]]; then + COMPREPLY=( $(compgen -c -- "${cur}") ) + return 0 + fi +} +complete -F _frun_complete frun + + +# ============================================================================== +# AUTO-BOOTSTRAP FOR FRUN LOADABLES +# ============================================================================== +_forkrun_bootstrap_setup() { +## HELPER FUNCTION TO LOAD THE RING LOADABLES USED BY FORKRUN + +# Define helper functions used by _forkrun_bootstrap_setup +_forkrun_get_arch() { + + local ARCH0="$1" + + : "${ARCH0:=$(uname -m)}" + + case "$ARCH0" in + x86_64[-_]v[2-4]) + ARCH="${ARCH0//_v/-v}" + ;; + x86_64) + if grep -qE '( avx512[cdbwdqvlf].*){5}' &2 + return 1 + ;; + esac + return 0 +} + + + +_forkrun_base64_to_file() { + local b b0 b1 k kk fd0 fd1 out0 out outC outN outF outB outFile nnSum nnSum_md5 nnSum_sha256 noVerifyFlag doneFlag IFS extglobState legacyFlag noCompressFlag + local -a compressV compressI outA + #local LC_ALL=C + local -I extglobState + + { + + # parse options + [[ "${extglobState}" == '-'[su] ]] || { + if shopt extglob &>/dev/null; then + extglobState='-s' + else + extglobState='-u' + fi + } + shopt -s extglob + + if [[ "${1}" == '--force' ]]; then + noVerifyFlag=true + shift 1 + else + noVerifyFlag=false + fi + + [[ -t 0 ]] && { + printf '\nERROR: pass the base64-encoded sequence on stdin. ABORTING.\n' >&2 + return 1 + } + + # determine if we are outputting to stout or to a file + exec {fd0}<&0 + if (( $# > 0 )); then + [[ -f "$1" ]] && \rm -f "$1" &>/dev/null + outFile="$1" + : >"${outFile}" + else + outFile=/proc/${BASHPID}/fd/1 + fi + exec {fd1}>"${outFile}" + + # read dataheader and data + read -r -d $'\034' -u "${fd0}" out0 + read -r -d $'\035' -u "${fd0}" out + if [[ -z ${out} ]]; then + # first char of data section was $'\035' --> using standard base64(+gzip) + legacyFlag=false + read -r -d $'\036' -u "${fd0}" out + if [[ -z ${out} ]]; then + # second char of data section was $'\036' --> payload was gzip compressed + read -r -d $'' -u "${fd0}" out + noCompressFlag=false + else + noCompressFlag=true + fi + else + legacyFlag=true + fi + + exec {fd0}>&- + + if [[ -z ${out} ]]; then + # if data header is missing then the base64 may have been made with standard base64 decoding. attempt to work with this. + out="${out0}" + grep -F '+' <<<"${out}" | grep -qF '/' && { base64 -d <<<"${out}" >&$fd1; return; } + noVerifyFlag=true + outN=0 + outF='' + nnSum=0 + else + # parse the data header to get various parameters + { + read -r outN outB + read -r nnSum_md5 + read -r nnSum_sha256 + ${legacyFlag} && mapfile -t compressV + + } <<<"${out0}" + + # determine checksum to use. prefer sha256 + if type -p sha256sum &>/dev/null; then + nnSum="${nnSum_sha256}" + elif type -p md5sum &>/dev/null; then + nnSum="${nnSum_md5}" + else + noVerifyFlag=true + fi + + + # restore full base64 sequence + ${legacyFlag} && (( ${#compressV[@]} > 0 )) && { + compressI=('~' '`' '!' '#' '$' '%' '^' '&' '*' '(' ')' '-' '+' '=' '{' '[' '}' ']' ':' ';' '<' ',' '>' '.' '?' '/' '|') + + for (( kk=${#compressV[@]}-1; kk>=0; kk-- )); do + out="${out//"${compressI[$kk]}"/"${compressV[$kk]}"}" + done + } + fi + + if ${legacyFlag}; then + + # recreate binary from base64 sequence + # this generates outF which is a string that contains the hex values formatted like: \x00\xFF\x9A\x...' + # printf '%b' then will write out the binary data using that string + while read -r -N 4 b0; do + b0="${b0%%*([^0-9a-zA-Z@_])$'\n'}" + + [[ ${b0} ]] || break + (( b1 = 64#0${b0})) + + printf -v b '%06X' "${b1}" # always generate full 6 hex digits first + + (( outN < 6 )) && b="${b:0:$outN}" # then slice only if it's the final group + + (( outN = outN - ${#b} )) # subtract actual hex digits used + printf -v outC '\\x%s' ${b:0:2} ${b:2:2} ${b:4:2} + printf -v outC '%s' "${outC%%*(\\x)}" + outF+="${outC}" + + ((outN <= 0 )) && break + done <<<"${out}" + + printf '%b' "${outF}" >&"${fd1}" + + elif ${noCompressFlag}; then + # using standard base64, no compression + base64 -d <<<"${out}" >&"${fd1}" + + else + # using standard base64 + gzip compression + base64 -d <<<"${out}" | gzip -d -c >&"${fd1}" + fi + + exec {fd1}>&- + + # verify output file and make it executable + if [[ ${outFile} ]] && [[ -f "${outFile}" ]]; then + chmod +x "${outFile}" + (( outB > 0 )) && type -p truncate &>/dev/null && truncate --size="${outB}" "${outFile}" + ${noVerifyFlag} || [[ "${nnSum}" == '0' ]] || { nnSumF="$("${nnSum%%\:*}" "${outFile}")"; nnSumF="${nnSumF%% *}"; grep -qF "${nnSum#*\:}" <<<"${nnSumF}" || { printf '\n\nWARNING FOR EXTRACTED LOADABLE:\n"%s"\n\nCHECKSUM DOES NOT MATCH EXPECTED VALUE!!!\nDO NOT CONTINUE UNLESS THIS WAS EXPECTED!!!\n\nEXPECTED: %s\nGOT: %s\n\nTHIS CODE WILL NOW REMOVE THE EXTRACTED .SO FILE AND ABORT\nTO FORCE KEEPING THE [POTENTIALLY CORRUPT] .SO FILE, RE-RUN THIS CODE WITH THE "--force" FLAG' "${outFile:-\(STDOUT\)}" "${nnSum}" "${nnSumF}" >&2; ( read -r -u ${fd_sleep} -t 2 ) {fd_sleep}<><(:); \rm -f "${outFile}"; return 1; }; }; + elif ! { ${noVerifyFlag} || [[ "${nnSum}" == '0' ]] || ! ${legacyFlag}; }; then + nnSumF="$("${nnSum%%\:*}" <(printf '%b' "${outF}"))"; nnSumF="${nnSumF%% *}"; grep -qF "${nnSum#*\:}" <<<"${nnSumF}" || { printf '\n\nWARNING FOR EXTRACTED LOADABLE:\n"%s"\n\nCHECKSUM DOES NOT MATCH EXPECTED VALUE!!!\nDO NOT CONTINUE UNLESS THIS WAS EXPECTED!!!\n\nEXPECTED: %s\nGOT: %s\n\nTHIS CODE WILL NOW REMOVE THE EXTRACTED .SO FILE AND ABORT\nTO FORCE KEEPING THE [POTENTIALLY CORRUPT] .SO FILE, RE-RUN THIS CODE WITH THE "--force" FLAG' "${outFile:-\(STDOUT\)}" "${nnSum}" "${nnSumF}" >&2; ( read -r -u ${fd_sleep} -t 2 ) {fd_sleep}<><(:); \rm -f "${outFile}"; return 1; }; + fi + + } {fd1}>&1 + + { (( ${#FUNCNAME[@]} > 1 )) && [[ "${FUNCNAME[1]}" == '_forkrun_bootstrap_setup' ]]; } || shopt ${extglobState} extglob +} + + local tmp_so dir rf bootstrap_flag need_memfd_create_flag need_memfd_b64_flag need_b64_flag have_memfd_loadables_flag force_flag fast_flag + local -a candidates + + need_memfd_create_flag=false + need_memfd_b64_flag=false + need_b64_flag=false + have_memfd_loadables_flag=false + force_flag=false + fast_flag=false + bootstrap_flag=false + + # check for -f|--force as input arg + while true; do + case "$1" in + --fast) fast_flag=true; shift 1 ;; + -f|--force) force_flag=true; shift 1 ;; + *) break ;; + esac + done + + [[ $FORKRUN_MEMFD_LOADABLES ]] && (( FORKRUN_MEMFD_LOADABLES > 2 )) && [[ -f /proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES} ]] && have_memfd_loadables_flag=true + + # fast "is everything already set up" check for runtime checks + ${fast_flag} && { + enable ring_list || { + ${have_memfd_loadables_flag} && enable -f /proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES} ring_list + } + if ring_list 'ring_funcs' 2>/dev/null && (( ${#ring_funcs[@]} > 0 )); then + for rf in "${ring_funcs[@]}"; do + enable "$rf" 2>/dev/null || { + fast_flag=false + break + } + done + else + fast_flag=false + fi + } + ${fast_flag} && return 0 + + # check for existing b64 array + (( ${#b64[@]} > 0 )) || need_b64_flag=true + + # check for existing memfd holding b64 + { [[ $FORKRUN_MEMFD_LOADABLES_BASE64 ]] && (( FORKRUN_MEMFD_LOADABLES_BASE64 > 2 )) && [[ -f "/proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES_BASE64}" ]]; } || need_memfd_b64_flag=true + + # if we dont have the b64 array and there isnt already a memfd holding it (to recover it from) abort + ${need_b64_flag} && ${need_memfd_b64_flag} && { + printf '\n\nERROR: There is no b64 array variable to generate the .so from and no memfd to recover the b64 array from. ABORTING!\nNOTE: to re-load the b64 array and setup the loadables again, run ". %s" again.\n\n' "${BASH_SOURCE[0]}" >&2 + return 1 + } + + # check for the memfd_create loadable + enable | sed -zE 's/\n/ /g' | grep -qE '(ring_((memfd_create)|(seal)|(list)) .*){3}' || need_memfd_create_flag=true + + # set ARCH + _forkrun_get_arch "$1" + + # if we need the b64 get it from the memfd + ${need_b64_flag} && { + . "/proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES_BASE64}" + (( ${#b64[@]} == 0 )) && { + printf '\n\nERROR: ring_memfd_create is not loaded and there is no b64 array variable to generate the .so from. ABORTING!\nNOTE: to re-load the b64 array and setup the loadables again, run ". %s" again.\n\n' "${BASH_SOURCE[0]}" >&2 + return 1 + } + need_b64_flag=false + } + + # if ring_memfd_create isnt loaded then bootstrap it by briefly creating the .so in in a tmpfile and loading it + ${need_memfd_create_flag} && { + bootstrap_flag=true + + # Define candidates in order of preference + candidates=( + "${FORKRUN_TMPDIR:-}" # user override via env var + "${XDG_RUNTIME_DIR:-}" # Best: Standard, private tmpfs + "/run/user/${EUID}" # Fallback XDG + "/dev/shm" # Standard shared memory + "/run/shm" # Legacy shared memory + "${TMPDIR:-}" # Standard env var + "/tmp" # Universal fallback + "${HOME}/.cache" # User disk fallback + "$PWD" # Last resort + "python" # Fileless fallback via python + "perl" # Fileless fallback via perl + ) + + local py_script='import os,sys,time; fd=-1 +try: fd=os.memfd_create("b",0) +except: + try: import ctypes; fd=ctypes.CDLL(None).memfd_create(b"b",0) + except: sys.exit(1) +sys.stdout.write(str(os.getpid())+" "+str(fd)+"\n"); sys.stdout.flush() +while True: time.sleep(60)' + + local pl_script='my $a=$ARGV[0]; my $s=($a=~/^x86_64/)?319:($a eq "aarch64"||$a eq "riscv64")?279:($a=~/^ppc64/)?360:($a eq "s390x")?356:0; exit 1 unless $s; my $fd=syscall($s,"b",0); exit 1 if $fd<0; print "$$ $fd\n"; $|=1; while(1){sleep 60;}' + + # try various places to make the tmp .so file to bootstrap + for dir in "${candidates[@]}"; do + local helper_fd="" helper_pid="" helper_out_fd="" + + if [[ "$dir" == "python" ]]; then + if type -P python3 >/dev/null 2>&1; then + exec {helper_fd}< <(python3 -c "$py_script" 2>/dev/null) + elif type -P python >/dev/null 2>&1; then + exec {helper_fd}< <(python -c "$py_script" 2>/dev/null) + else + continue + fi + read helper_pid helper_out_fd <&$helper_fd + if [[ -n "$helper_pid" && -n "$helper_out_fd" ]]; then + tmp_so="/proc/$helper_pid/fd/$helper_out_fd" + else + [[ -n "$helper_fd" ]] && exec {helper_fd}<&- + continue + fi + elif [[ "$dir" == "perl" ]]; then + if type -P perl >/dev/null 2>&1; then + exec {helper_fd}< <(perl -e "$pl_script" "$ARCH" 2>/dev/null) + read helper_pid helper_out_fd <&$helper_fd + if [[ -n "$helper_pid" && -n "$helper_out_fd" ]]; then + tmp_so="/proc/$helper_pid/fd/$helper_out_fd" + else + [[ -n "$helper_fd" ]] && exec {helper_fd}<&- + continue + fi + else + continue + fi + else + # Skip empty, non-existent, or non-writable directories + { [[ $dir ]] && [[ -d "$dir" ]] && [[ -w "$dir" ]]; } || continue + + # Generate path with high entropy (30-bit random hex) + printf -v tmp_so '%s/forkrun_boot_%s_%X%X.so' "$dir" "$BASHPID" "$RANDOM" "$RANDOM" + fi + + # Try to extract loadable + if truncate -s "${b64[$ARCH]%% *}" "${tmp_so}" 2>/dev/null && _forkrun_base64_to_file <<<"${b64[$ARCH]}" "$tmp_so" 2>/dev/null; then + chmod +x "$tmp_so" 2>/dev/null + + # CRITICAL TEST: Try to Enable loadable + # This verifies the filesystem allows execution (noexec check) + if enable -f "$tmp_so" ring_memfd_create ring_seal ring_list ring_pipe 2>/dev/null; then + # SUCCESS! The builtin is loaded. + need_memfd_create_flag=false + fi + fi + + # Clean up + if [[ -n "$helper_pid" ]]; then + kill "$helper_pid" 2>/dev/null + [[ -n "$helper_fd" ]] && exec {helper_fd}<&- + else + \rm -f "$tmp_so" 2>/dev/null + fi + + # break out of loop if we found someplace that works + ${need_memfd_create_flag} || break + done + + # If we get here and stil dont have memfd_create we failed --> couldnt find a writable location + ${need_memfd_create_flag} && { + printf '\nERROR: could not write and load bootloader for loadable in any temp directory. ABORTING!\n directories checked: %s\nPlease specify a writable directory by calling "FORKRUN_TMPDIR=/path/to/writable/dir _forkrun_bootstrap_setup"\n\n' "${candidates[*]}" >&2 + return 1 + } + } + + # if we bootstrapped or if force_flag is set, forcible re-create + seal the base64 memfd backup. if force_flag is set close the previous one + if { ${bootstrap_flag} || ${force_flag}; } && (( ${#b64[@]} > 0 )); then + + # if force_flag is set then close the old base64 memfd + ${force_flag} && ! ${need_memfd_b64_flag} && exec {FORKRUN_MEMFD_LOADABLES_BASE64}>&- + + # open a memfd, write b64 to it, and seal it + ring_memfd_create 'FORKRUN_MEMFD_LOADABLES_BASE64' + export FORKRUN_MEMFD_LOADABLES_BASE64="${FORKRUN_MEMFD_LOADABLES_BASE64}" + declare -p b64 >&${FORKRUN_MEMFD_LOADABLES_BASE64} + ring_seal "${FORKRUN_MEMFD_LOADABLES_BASE64}" + need_memfd_b64_flag=false + fi + + # open a memfd, extract loadable .so to it, and seal it + ${force_flag} && ${have_memfd_loadables_flag} && exec {FORKRUN_MEMFD_LOADABLES}>&- + unset "FORKRUN_MEMFD_LOADABLES" + ring_memfd_create 'FORKRUN_MEMFD_LOADABLES' + export FORKRUN_MEMFD_LOADABLES="${FORKRUN_MEMFD_LOADABLES}" + truncate -s "${b64[$ARCH]%% *}" "/proc/self/fd/${FORKRUN_MEMFD_LOADABLES}" + _forkrun_base64_to_file <<<"${b64[$ARCH]}" "/proc/self/fd/${FORKRUN_MEMFD_LOADABLES}" + ring_seal "${FORKRUN_MEMFD_LOADABLES}" + + # get list of loadables + ring_list 'ring_funcs' + + # unload existing ring loadables + if ${bootstrap_flag}; then + enable -d ring_memfd_create ring_seal ring_list + else + enable -d "${ring_funcs[@]}" ring_list 2>/dev/null || true + fi + + # load ring loadables exclusively from memfd + enable -f "/proc/self/fd/${FORKRUN_MEMFD_LOADABLES}" "${ring_funcs[@]}" ring_list + + # clear massive b64 array + unset "b64" + + return 0 +} + + + +_forkrun_file_to_base64() { + + # local nn kk kk0 k1 k2 out out0 outF outN v1 v2 nnSum hexProg quoteFlag noCompressFlag IFS IFS0 + local -I extglobState + + # local -a charmap compressI compressV outA nnSumA + local LC_ALL=C + + [[ "${extglobState}" == '-'[su] ]] || { + if shopt extglob &>/dev/null; then + extglobState='-s' + else + extglobState='-u' + fi + } + shopt -s extglob + # parse inputs + + local quoteFlag=false + local noCompressFlag=false + local legacyFlag=false + + while true; do + case "${1}" in + -q|--quote) + quoteFlag=true + shift 1 + ;; + -n|-nc|--no-compress|--no-compression) + noCompressFlag=true + shift 1 + ;; + -l|--legacy) + legacyFlag=true + ;; + *) break ;; + esac + done + + [[ -f "${1}" ]] || { + + printf '\nERROR: "%s" not found. ABORTING.\n' "${1}" >&2 + return 1 + } + + ${legacyFlag} && { + + # define char mapping array that convero 0-63 --> [0-9][a-z][A-Z]@_ (bash 64# chars) + charmap=($(printf '%s ' {0..9} {a..z} {A..Z} '@' '_')) + outN=0 + outA=() + + # to dump the binary as ascii hexidecimals , we need od or hexdump + if type -p od &>/dev/null; then + hexProg='od -x' + + elif type -p hexdump &>/dev/null; then + hexProg='hexdump' + else + return 1 + fi + + # map each 12-bit segment (3x ascii hex chars, each representing 4 bits of data) into 2 base64 ascii chars (each representing 6 bits of data) + while read -r -N 3 nn; do + nn="${nn%$'\n'}" + (( outN = outN + ${#nn} )) + until (( ${#nn} == 3 )); do + nn="${nn}"'0' + done + (( k1 = ( 16#${nn} >> 6 ) )); + (( k2 = ( 16#${nn} % 64 ) )); + outA+=("${charmap[$k1]}" "${charmap[$k2]}") + done < <(${hexProg} -v <"${1}" | head -n -1 | sed -E 's/^[0-9a-f]+[[:space:]]+//; s/([0-9a-f]{2})([0-9a-f]{2})/\2\1/g; s/[[:space:]]//g' | sed -zE 's/\n//g'); + + IFS= + out="${outA[*]}" + unset IFS + + } + + (( outN = ( outN >> 1 ) << 1 )) + + # get orig file size + if type -p stat &>/dev/null; then + outB="$(stat -c %s "$1")" + elif type -p wc &>/dev/null; then + outB="$(wc -c <"$1")" + else + outB=0 + fi + + # embed checksums + if type -p md5sum &>/dev/null; then + nnSum="$(md5sum "$1")" + nnSumA[0]="${nnSum%%[ \t]*}" + nnSumA[0]='md5sum:'"${nnSumA[0]}" + else + nnSumA[0]=0 + fi + if type -p sha256sum &>/dev/null; then + nnSum="$(sha256sum "$1")" + nnSumA[1]="${nnSum%%[ \t]*}" + nnSumA[1]='sha256sum:'"${nnSumA[1]}" + else + nnSumA[1]=0 + fi + + # compress base64 and assemble the header + if ${noCompressFlag} || ! ${legacyFlag}; then + printf -v out0 '%s\n' "${outN} ${outB}" "${nnSumA[@]}" + else + # initial compression run + : "${testFlag:=true}" + compressI=('~' '`' '!' '#' '$' '%' '^' '&' '*' '(' ')' '-' '+' '=' '{' '[' '}' ']' ':' ';' '<' ',' '>' '.' '?' '/' '|') + compressV=() + kk=0 + for kk0 in 7 6 5 4 3; do + mapfile -t compressV0 < <({ sed -E 's/(00+)(([^0]+0?[^0]+)*)/\1\n\2/g; s/([^0]+)/\1\n/g' <<<"${out}"; sed -E 's/^((....)*).*$/\1/; s/^(.)(.)(.)(.*)$/\1\2\3\4 \2\3\4 \3\4 \4 /; s/(....)/\1\n/g' <<<"${out}" | sed -zE 's/^(....)\n/\1\n\1\n/; s/\n(....)\n(....)\n(....)/\1\n\1\n\1\2\n\2\n\2\3\n\3\n\3/g'; X="${out:0:1}"; while read -r -N 1 x; do if [[ "$x" == "${X: -1}" ]] && (( ${#X} < 32 )); then X+="$x"; else (( ${#X} > 1 )) && echo "$X"; X="$x"; fi; done <<<"$out"; } | grep -E '..' | sort | uniq -c | sed -E 's/^[ \t]+//' | grep -vE '^1 ' | sort -nr -k1,1 | while read -r v1 v2; do (( v0 = v1 * ${#v2} - v1 - ${#v2} )); printf '%s %s %s %s\n' "$v0" "${#v2}" "$v1" "$v2"; done | grep -vE '^-' | sort -nr -k 1,1 | head -n $kk0 | sort -nr -k2,2 | sed -E 's/^([0-9]+ ){3}//') + compressV+=("${compressV0[@]}") + for (( ; kk<${#compressV[@]}; kk++)); do + out="${out//"${compressV[$kk]}"/"${compressI[$kk]}"}" + done + done + + # 2 final compression runs where we re-generate the list of possible replacements and expand it to also look for simple repeated chars (with a limit of a maximum of 32 chars) + for kk0 in 1 2; do + compressV[$kk]="$({ { sed -E 's/(00+)(([^0]+0?[^0]+)*)/\1\n\2/g; s/([^0]+)/\1\n/g' <<<"${out}"; sed -E 's/^((....)*).*$/\1/; s/^(.)(.)(.)(.*)$/\1\2\3\4 \2\3\4 \3\4 \4 /; s/(....)/\1\n/g' <<<"${out}" | sed -zE 's/^(....)\n/\1\n\1\n/; s/\n(....)\n(....)\n(....)/\1\n\1\n\1\2\n\2\n\2\3\n\3\n\3/g'; X="${out:0:1}"; while read -r -N 1 x; do if [[ "$x" == "${X: -1}" ]] && (( ${#X} < 32 )); then X+="$x"; else (( ${#X} > 1 )) && echo "$X"; X="$x"; fi; done <<<"$out"; } | grep -E '..' | sort | uniq -c | sed -E 's/^[ \t]+//'; { read -r -N 1 y; while read -r -N 1 x; do if [[ "$x" == "${y: -1}" ]]; then y+="$x"; else echo "$y"; read -r -N 1 y; fi; done; } <<<"${out}" | grep -E '..' | sort | uniq -c| sed -E 's/^[ \t]+//' | while read -r v1 v2; do if ((${#v2} > 32 )); then (( v1 = v1 * ( ${#v2} / 32 ) )); v2="${v2:0:32}"; fi; printf '%s %s\n' "$v1" "$v2"; done } | grep -vE '^1 ' | sort -nr -k1,1 | while read -r v1 v2; do (( v0 = v1 * ${#v2} - v1 - ${#v2} )); printf '%s %s %s %s\n' "$v0" "${#v2}" "$v1" "$v2"; done | grep -vE '^-' | sort -nr -k 1,1 | head -n 1 | sed -E 's/^([0-9]+ ){3}//')" + out="${out//"${compressV[$kk]}"/"${compressI[$kk]}"}" + ((kk++)) + done + + printf -v out0 '%s\n' "${outN} ${outB}" "${nnSumA[@]}" "${compressV[@]}" + fi + + ${legacyFlag} || { + # new method using standard base64 and gzip + if ${noCompressFlag}; then + out=$'\035'"$(base64 -w 0 <"${1}")" + else + out=$'\035'$'\036'"$(gzip -9 -c <"${1}" | base64 -w 0)" + fi + } + + # combine header and base64 + printf -v outF '%s'$'\034''%s' "${out0%$'\n'}" "${out}" + + # print output, optionally quoted + if ${quoteFlag}; then + printf '%s' "${outF@Q}" + else + printf '%s' "${outF}" + fi + + + { (( ${#FUNCNAME[@]} > 1 )) && [[ "${FUNCNAME[1]}" == *'frun'* ]]; } || shopt ${extglobState} extglob +} + +FORKRUN_FRUN_SRC="ulimit -n $(ulimit -Hn)"$'\n' +unset "b64" + +# <@@@@@< _BASE64_START_ >@@@@@> # +declare -A b64=([x86_64_v4]=$'0 145992\nmd5sum:64ed31e2b97c37ead57b70c5a7e07bc8\nsha256sum:92e30fad3a53b39c03a51777684490ac80500cd7fe4b44f3f18dbad568aa4fab\034\035\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/QcfGUnI6zOQwSiv+GnFp3HeY6An2SuHEBS481s0Ga1J22KpGS+lDFU7JjMxY4zBN6IZC527KHi2Ru42FFShz2fu4GzqXU49F4qFIMofB0Jwh9YfyiXW7bAv2Sd/akB3ymAIhln/TS4725gvFSdCcWA47SnIV589dA5w0ThT4noy4PZfWnKyQFe24cYSha8SCLrj7hcwI/mTA7iD+BsbxKbmiXO+Q4xwfIgtKwrASRaYkIml4qDzn7uS6aD3w4v1ZWA9DcdRqfWExL1uIHzKoWKHW5gfFvdhRu7cQst0GHEmcY/8bevPzU7eH2Eiazi15+jhSg+QAtRAdUcOUuv5/LAfBzyEbOnRehW4Km+4ClIkC3LsV3NWWz34fWM1aqTsKfA4C97RZikgGUJ/rE3ZCVA53s7MfdGTLBavAbxyFTM/0L7GdS+/1T8k9IiybVS4cm7pMKGSEkok7a2ZHWBDn7pzDqwBqsnitc4Q++jPS9ncAa8a8ru/YDkGfwVtISJHM6Kha4nxkeYlBk1waAyAQBXZukB7YRH4d2w99UX4OHEm8RrvGQibPOX9uMBufl+ST6LbpuaOOhH2QTY4xlgzu6C6iZ8eK98Shl+FADhK5h+AH05jzxaPDHUkeRPOG3DuYCKdxUpcCTn14orXvtgKK5OFCqGD2SknXCMBg3tgfvhS4n+hK/xnXKnzXrXEBGANdlmBd20LwBmkY0BpucQf/ck354ZLoenVHDYt0+Lh4ez4KHLU2KGBtn7/H0nJ0SYfCdmPOjv+xj7NRPGl8j0RQ0eyoXD4fM5Ke9TXjjC5+NPsEGXNR+E5qNs4u2/Yu0DWTYrQCCDv1Ht73umC35r+oKaDui/Uj7g7b1h7RO09oYRFWN7x0OOBx1yHeDHkk2CCUB/AQASr2QAhGHWz0F90m+IuPuUW6gqn4yBiVD/4iZWfyWrRyhndYTu4x8h3ZjPd906nMRnCn3+FbtLLs/w1mW58pEUuuzlLnFYufEdExbWjYZ3qEZ9Gl4kfFyH9gPlMdbPrHzHOuyg5of5aUHFBZUuuUxCS/LLhAKWVwAvJX+i5B8o+YJZ96ZV6vgleYqtkjzaZlWGHMZ9Cb+wVWB0hABNs6vzkQy75dMu+45ZnfkA1euDOAq2n1K2uuTNbtxE1WZ3CvxpMNfsDK1XPtLDmjL9e44HH5DPA7ScGxl0lZrDCC7R+xatTv8iDsXfqTo/OAug+CzUd9/I6tcc1qGb/VC690T28zDjh46GZryJzXiuaJzxrLQTGr49cgin+ZKVJh6YbKFpqqFpnpzlBnx4TF8vhL1SdwTtHJJQAA8YPWDruPcIX8fVyNmghb3C8ZgkDi8q1uGbol4Kn49C8GHr+M4Rvo6EB+pLIfgS/NSnkGDQdx3yaXHVLXKDfNqjTs82i6vuFpx+S1MS4PyGrCG4eSV5p1yYc4cp253TKIjer5BfNYIahB9y0K+FZLCoDprEIHXvmL0ePcfqD/DvIEFcUIBehOpuzpgC2bIYekY89LSkZt0vror2NPQVfR9jn7OEVNH3Nv0CVcrnp+/AB98X+Ae/E7QPvhhp/GC89sGajInzc14UTNmf44u+B2GSrP3tAmsvmprzUeao6R7CH2pwhH5Vi/nol6RxNlwTgXslUVs3T0PvrJdwsN7XoLPVyC/S6pyy2xYL/7c6ZafNrKw4QMq1leRyJ8hESLicUBMriRkVNBlHBJ/MCxHat3eFQS9Hm4wkJ1TBGNRnaO04eHAhGXiew1/Y48/aelTqs3kurMd0fT2ug3eccpHDc1r4CR2sZIPyHKhFo1mGd4Po641wkivUphYdX7De+wLvsBbhh2LprhYdf+iLtxkBjCJZfgunK+z5Hxp8ye/9AT00wj/e+D6aLaaHv/+T9j75DR8xvA9wSRN9k1s4XLwK/FIfDY2f5rgOsTKtci3+dsqFs/cHTbVBT4s168rC6niaIQYgzN6AUHLI69UmNGnICaOujmDz/7v+lPYTNtkJTTJSC+DXb80hqHbkFl8NquqnLaGH6LMkG572MA8eUv92wQBf1HhmNPMnqcYnqFL8vZkhdXaiDq8cZHMJH/QAZHGwgb/agw98i8nwupW7rOn1BAJnDrHIhJH4roW9OxB+Qwshu4PDU12bT/LmsYs02fw8KNRsoQmuw30HICX1Fi2ONLN1iG5QS4aRN7HWympzTGupp1fI4AmoaQrGNGh46b+oVwJ883R8bdTrYfSAsOo/jRUwGNUcNFR05C5rvQIATgav+Qb5hfjxAy55O7pLpdnHE1FNnAk7FAWaaAF5htMW75Lr0/aA+CLJZptbPpaPwqvk72fzQ0t3yoF7ArE3SPYiIMwVyoVqjVdM7519r+fCeHEe+gHSCjLth8W3C+qrpNkl+BGDWZvkiPv/BGIBZMWcZfE0tM9+YR2SFOXE/mAw03586ms1a9n+kvx9bJJcHOKv8m6QadYh2JXFfzKho72UUpx1vSSU1uyfr1z4I6zfa1i/b0O/NUh3M4VzaXtqFun9kcldHaPzA0+xoCJtgcmrAxC6GrQc8sUHJPk88NhtKMHUdODjg0/fA59m43LKR5V2bFQzDitT9KHsx6H0W43fIoyRAjORaE6wWUEmjEVsUcbvgxH+NB/lE7esaNAqxrJUXmB0DBQb11NCO/FR/AEzwXiT4CzJXivmLqW1dslbmGtcH73neLJbo9jxIKeYQcquigIp+y0ctlzs9n8xiQaYIUh2zxRUOHIX4nrugYbfYsOnqOExVyCrBxCTo1LKbsmfNw7fEXYpJ/ayJRkget+kqmLJXiN63mGawrP4/o3wPv9KzbL5tJmKDfLowD0kX2ah2JZMTw2YM3F+JrDlaFc5hWmlFRTPdwf+g8jplk+55Trl5J+IjKUoUBdIsge/4ZZ/wFmoAxkfgeFM/dQIv8DgXRYY1YI/cFQr6A3hbFkkCI97p03JBFkn2ymunWAzp52ouQ7eL8Mez8BSp21wy0F3YIoggcCuZMCo8Y0kwAOnfMQt17tTzijiHwSN7I2OnDuBZyXh9gK2aMXxAYNLximmFRgdPidq9nK8Gg/rk3YC5Fl3YFyE+h9cCKoPxJpQ9JFgy8lZNpBO3LZ4mEQXnMSWPSiLYYUfH/nzR9GOyRsDfwAsyhY2HtGLzhOX7MPH4tosQAJ5Nx/y2D0aBEWvjDhUlgHvBty2FpwnKCOC9sUlZvjio6Ev5owiaPdbnxnIFgAWogfjwVA/xIb9qGEOjsRtr54m4wd8N+N+QIHkJ6LtvaGIYEXwAnCV2l3wDnxVLUeqiSD0/tJCXV6PXe7fDbQi0Odm/ukRcj+lpsITFMR59ajopQEGHJY8h6qByiWZEfKvWNPqlKsABhQVklfA9Zek1WQ8c9q6IEStypPQLxA6KDlticpVu9kMEyXfBnHeXBLxGwUEsFX0foQceKYt6TrR+wP15oABN1wjzvER4NeXNj8bd2MlStpnSvef2lNy4OW/JbyIZU91tRQYFMWZtAEfSw9nRUCzKwqyQRkuSio9//tGyd6UrUj2wqx/lja8kDMoypR1i+QpgO1ZOOv0htb7p3U5raDmV6S3G2Cz4N+S/Y2vrId+alYxPEsrgPH37Cn6MNhvQzE+WWakL56geVZ71imTRx4i2Y8H3DBl2hn49CJIpJnjDwGokwUd1CYC3UvxXFpEDAxUIfHALeAfmugUVw2AxfxbBCxmF1xrhrDATdz2xWOI9LxMvQ1NcsqTbWZn4PGLkhztabZkDXbKhx2/kAZaeDgyfD/HYH8l8KER/qzeSSHsSHZ5Sq0u+4nsPbR6sMTmtA0Oce1ON6B3YoZcjQp6IhGhz5pIifK9x3r8UYAep0KPMEV35ATAhcAa22J6NtmWhNuFfeTucnM1vV8Gbdd2pAasoVKym6imFFhJZVCyOu2A/vy0B9M2pFWCjpUcEUGcoYvLn+r2WxUTwASGRKGsQDFug0bA+lCIU7Zv10xWs0sQ4kYaSeuknN3O9PSNiMrwJiB6vPIM9OhpCGbtN3T12nYyg8bLRZ4Ds7LuCgwRBgmvfBLIRcysWXx3oN9hiseVaUWUubSA5UQfUBp3yXMolushEjnTTeKq33uZQPwQM4oovtQTjGwbf1xynYZCgUdbpPF7AHfyQrhTshP69r+i4Q7hjDJyB36wHFakF4jhSvUOA86USPaFDGd6wrQAVZrT9rjlw67CQ5FGfHb5nVcD0TRfw/TVwX8EBZPyrrGjUpf9j+wqafwJqdx8ysSZdbJy3Q6GEihSAkj74NKnkpq6NhqpS2CRLYfsKTsRQKeU8b8DWLNsyQjpU4qvikp98PeTCELAC5R0lUU7DJhCNe/D47QgyhOAK1SjbEO6iMPoDijEcQbwpQHGzlFl+w6iWckOuUR5cjsbwRu/oxv5UNYgHK5y/3ZCpiQiCjCmvWz1524LIVJeOCLRepG4si5Ow3VlEXTjxO0DEHf5fcj3M9JO4PIkIbNMzZQb/KNtfTIApTdkpigkE9Urq7YxxpOHfCyrvUsozbQ3T90G/NQtH6HelaHbaQZ9lK9+Dw20poPSexvhsegbHqQG3Ql1laU7GCbvM8yloJIwOYlh8uOEyeK8q+E9hs1qosHOEuj3J5MnCWuUldtDeH2cuKPXRoj9fTPJDconlXwcd6PAODjI9TMjvv8E7z0gN641kV1QCiS8Xoyk/zCTuR2jUd7+wmIgCs/iwtZhU17xynZCsrxq9FIV/5RDBHx1MJK/A7XuwFL6e1ZaBqCT9yk/Qx/yPqStz8GvTN8Jcd4SeF7aeKrADQJmohvQJkkS1y6i10pbZgGA6N90+ncc/OslzPXuYb4LVAASHb/gurvWtmAI5ylOs4E5zFcG0l4x1fQxbCrj/gIJgb7rEtd2t2Gfq9EM7hwjWLMOEt11y0dpUyv7t6HIhdRULpbLHTmDbH1F70pck/Eoqbfd/2AExgvxIP6UFDXWb5cKT0a5YrrUI0O0l7+8n76ac6HPC1Eu8ZO90/q4YDICyOoh/oCcExk7gCQRcBjb1mDbqYdhsL4eqAgY6YVbblqbwwh2GmAA7BJcwUe0TaLbXWlqLoC1QJOTQKdKVIKVfIZyub1YfP3viDnXwD/IZT8jzaPmGySaYfJ8UPR+LmiKmmO0Sz639hGUZ8h2CvwVUF2J2opLwqS0TrhmgAiVFcFgzszI4KOiL0gjOIai+eymIEUzbGfGbYmwAe2TJLbeVKnZKOVTZc4uSUAPKpA4jYGJXmAvLtKVLkRBFGGVBvw6dlTm7Z5EmthtW0K7B8Mb/MOTMdQF7VpfmLPGhhjro9gQWFEigxLvsZyrdsXKb9T1XKpFEdePK2Vfn9UtZ4Apu4tn4LVZIkqIB+jzyqmttCIIktZ0i1fDHgHYpFWGHqt3bzU6CzLSYJvsJzFQCixg85MAMWs+53I4fehIaH4+PPVQI2vvF7davwfIAIl6lqTEVzJrZnuQ86VHHqWmwMoCgz8G/TWtQJkPI5GLcb/P0ehrTYJmV711M6c3r2HU0zW6LX/TFqZh7ZX3Mab44hZtDX2VWem0igYIAx9I2cwaJIqrOnkO7MtpuifrSUkulAr3d8lpypREZyHN6yFCfWaHfXArG3lPHDmoG5HoBCF4wAhi4IM1OzV7Ltlbr2ftZ1WQvU2NNdDZwup2NR+H4ENYHBj8yQ8oBB8fpcRW0JtZD+UMSMu+L2e6YMp2r86BVViba3Kg7DX/B4LVhAr0+oNafW3Y09fZ02H8qZhH6OopGSVXPELwhjYPQRtlKQNb1s34nRvpO7bVUWxTrLuLCLZi2sK/sTY03tUR4W3+2MzbvK+88SuuUFfR50a9pdLQ6MfN2nDScMtPDobsdaWNz1qSQX1FvIqX8m8aQ/8RvbASFy1tBKocr5z7DRcNKn0FctH0buRRSIUP4kKrV4Xgi/0pZYIJOSZ2xF//j/H1GYWqqtsTH0RBvCWtwPEAgOaB7wUTGYI8JTmKsAWZz/SXQYaQ5IM1nZkcuWwTx8Ov0O47i0ED7RxDftNo0PTdWD7zK0L4RNbgMnMf08TZg2xP/0P0fhoyFiON+mgTMjz4cN13AopaACs/wAq+CMCSrxRMbH/8uIZWdYr+KC+D6MFBkAeu0sZzY6vxfP9r+Hj+ycYjemPCxoCjU7puYlouoKv3wKjJR2a67YqYW23i33+Cfb/2N/79GVeoJaSAo/9rowYPU/j3b2n1/QOb+PdRjcav0ucZ63sHOnGllOYThxGHKGkFmfJNsB9ydBuPbg/pzb6XfZPxW2Wb9G9R+Xn2reyF6houh2PtOKhVl1EFlUdhK/hIWJgp39egBUZMF314BKpmj5Ge3c9OuA3eFI2OymDWzf7+1fjzyTrTuMWCNLvMNCrepPhw8uWWJdHsVB38LNd++gdXs1dF72gBHeT/jqbDG8Tq0/a0op/+QR9LgT4fksoTnG5RFm0k73Z2NHOTxvoHJVO9l9W/3Lp+Mqt/tHX9aFY/uHX9IFZ/OKpVvQ3rPcXCwB5n8JF/8FXwppj7KEBOmb4e3xm8Hx+UW1qiIjTOnRWvjF1PgCiM0me/OyqCP0tnz0pDz1bpz2zs2b9Dz95EY1kc+9Qw9qmX+FOlrpxa9w617qf3tJs9u4Y/8w/uWy8gLEVl1AZ0918JRUQA/+Du2oPb6UGM/iBYxx9cTQ+O17EHsDPGfgO0dP0G+v13/L0Gf3tKUJV6/Bu08qpfbTDyVxBjZGz8KDxkttTz3PJs7QQTidvIyLIEZFn0bifhuP9d36DYXK4kbUCClN0H1ufTs4JpNYavcfPp4CRoU26528ICzCRQgQ5AVzXtyi23WdjEyyw34C+3v1eiBQNDruT1DjIRJePpgMDwFrc8GeW2R62ZgazSeCmw3IYOHmTDIX+u235W9Kaj8O3vvbo986vmf01GR2V5GY2xyiGueqB9mWWlGQbkCmS0L7d8ZWZj81ZmXROCR05TH5DvkJisGiWgMOqtzK7JBC0N5WLl6jIEfxa86ZKbpcKjEcofiACy5QGqKiEBa0kUTjhSCkxvL8lraLwZSGfuJbP1iXDRmUsBJxVPaTA4VDYvl/zslZy7+mQNcYEQ6BzYNxJ6BzjVRkaYpm5WY5gxPCQveyz74YkgrorH8Ow7kKXdrek/kqdc4L38Ekm9fAV/tHFNzdHg5yugKOz3qA2GP2wQvUvRaOQ7JHp7dkSYJuCark3iciER4wLFXUa8FVTharbw9ywHrJuDOO6Puz0So+sz6INu2xi00Hn9sLB2y2Coy7KiWIPnN1CMHENri2yES5ugP6O9pTwH+WhQm4+/R9Q5wVTTSae/y0oY/e1qiKcYXsbjKbIr/D02nw1r/1Ib7a8wtl8S3v6eNtofLQ21HzwRRgnLmpFW5wtm36/m4omla2DcufOdJo78CY/RTLwRplFJ2uTuj+AUbYi/e7JvjyhPR6expwxXy+wc2F+E56KnHxlGLV1bN/5XBNVf37rez+qjWtcfZPVHhFb1b0G968lSU+IkHCba0aRycwQPpPlCYKPO4Wf7oOptXqWdw4aqXK2VQ696Vms1RK8aC1Vl3oj3h7JipvZSqMUdvCpvqF51g1bl1Ku6sH7e4/1YWPEDXqwzsRfmh/o4aKIWC3mL33mLnAy9RSGvygtVfaP1E6r6gFctDFXlQRXOMvSx53lNaLwTWE1OqOY+raNQ1V1YJRRJ/tdMGYhjr+UMZfNn9Tmr0zMosuxzdIH6X4tnjRC/1I+bkQPsDQq0Ijqhyi4MBteR32pgCRGoldCCqBOuLtth/rhlUKledxH0UpC3RW+/JqAc3ZuYPeX+Qi5HvQ1fMOB+TRHXb0TvSzQcywzoBfGpZhe+d5X2Xnb4ez+E3nuEvfdk2HsHC/h7T4e/91LovfvZez3D3lumvdcj/L2hofci2XunW4zvTdPey4P5k4eB7HkRpEJF8Zd3id4nL9LLS7WXf08LKkeLyBdH8Hy8M77ppTdRQYhHObpuHTMhVsFwfkYqoHgLWdiPlAAf2CX5x6KPJqHucxRk16abmIkgWMAVFaCjx+CRcmcRffwa+LjWCN468Dl6e/NSM4gCbzS89Cu+FAMvpRWAgo0c3KB3w/PHviPB+fN13KhYs0su/qknqdkbHCR2Sk/uQblxdSTZVGTLgmbUhX4gIbK6EKddKHkaQFasE3E4ltH0/C18jvLzFimQg7/hyVPwRHm0AIUdnYSXWwZBbc+eSZzLW+NBDvDa0OrYjrg9qERjXIGnrVCJ4qcpMzChNN6xFt91lZfSAEGTms72zaOcewb6n/6URUutXcug/DyqFFwSqObPlvBnN8I7qzuwZxX82Rz+7Dp8xuLm+hfzZ0/xZ73xWQx7toI/G8Gf2fBZLHv2EX92C3+WZOjzdf6sK38W3yHU50z+rOkX9myWoc+n+LO9/FkfMdTnI/xZEX9W18Gkw0Xizz7jz77vFHrvdv7sNf5sHj5jhuT+Nv7sGf6sAz6LYs+68mf3sWe+Nzui1fOlqJqOTJ+/v11aHeyRobvJOQjCxWGmtrhBhR7jt9x1AQWz5WTSdHhaAJP24snJYjxQ5Xsihh3gjph9EJa6BbbT5EKlm+y1rdBUv4tLBJPco6kJcMuxkyuryhJUVsuV+VW84umlpL0q12gtxi7FMZcqz1RhuAvWrKF3SpSLO7Sar5YIJmaxkaCVvNuNqrzngIh1U+iozeY4NLgpsbjtfJVZsZ6mCNpFLtFZLu8uPGaG1tTwBmr4aayJYkqJ5UP7jtB+NW+/E218SfiSVXtpSyy+NCaWThBCc1FrLonO7S55BzaO1Rq/T427xtJhSu+KWDr6w1tnHMOm8VpTmZpuw8OvaXuM/cIwKl3yNmzcRWt8HzWe1571+1aHUL9uMaPSZS+dFumWFffAybYk0bOsHRrw4Gem/dy0yEz5iMt+XPR4qfYw+mSnuO27xNzxWGHfKnpGtEP/zUZ/j1sbBTy57h3YAdWyAuq/pLDxmUqH/AeGolEYpFteZEMXcKk6eaNkL3XLC2wYduP2942H1yVxWKkEVXmElExydMsrbfnkwK6VAGcWUvgI9CQu8Nowat5lLyptnDWXTPkucViR216F7eabWlFwbL+KiGKd5PfSJ5haY6+aagVSW3+WTJ9uWxLzzNh3TbVK8np6kvlkC9JPh+eicE9g9GDoMNeagdoEw2FJ/h5ZfF5uOq9EKie+nTuUKp28EulhXm5GBpOMp0MfSfSbOQKgOACK5bmm0YsFM5Mmm0E39GfZJruFBgw4eYxUkLkMfo3PepkzVM4jyQHqccqlTbNykkmSyEuk6jwcqGTPM9Eo5hIIxAU5Dhxa3hB8Vp4Tkmkt/4RPpm1AadI8xB+7AviStAzYFInw8ingMmmryc+FDhQlYw2zd8X/RBy2OK3grLQMBdAtURiK2KsndJaBqoYQTZ1boAwrfT3+kU9nyPslwLNxGczRmDgSIesW1zIl5hcidp6ZtkSQYX7Fw9VydaZckymfqxlJOkPbnoq2fw7PW36tadRiiqTItO8XvR0RsbRPOey/On5B1ri6ixa75xSdCmzQDG8wq5jM4UP8gxajMQUPhBOfh50+ySG3YERPKupBA9zyWFu6G6ol9MQku+Q/nHkzbdZMeYszb7LtIVAmDPE2/0LIiWvHoks+taaDC3/S6Lx7sm6ocz4mJGXVSHJVTRdmJ4LnTv68ICu6zjlMSMquAeXXbMPA9Twgbxn2k6DhApi8Bdn/Ru9HMoaCpmbKjYjSA9x+HBzQPskproLRhAPkV9F3CkM8/LgacolL3pwp/+mWN7lAccmwHxFzN6G4JO+jCDsJ5mlVjuVzUyfVoVVPtjxzHuj31lYPSuBBX3yQH/YABS3Z0g8ffNzqAXbVGR/MadVVOTw4A3qi8nQ++twOQfGTc0jwC8UFBeiDW1AUUyEB/rG/rJwJq7agyFoh+vpYUJTegPCwit6rLcjg+gVwOdYGyed0imK03PIZZeaPyNnO8PqjymRDGbnk2LDyKcVNZb1KGfQjHznUZKQFWeUNUFnjhG1wEwx6SLmZSWZ+y76zoaILFHvnwMEKVImeuyxEGK84h4JhDyv96dsIj9YKVivIcSMCtl8ImzJ/wogeqnMLh4fKzl7wXv8foWWmcES5GZ+yNxxylJIUKg6Rzdcp8VCWM0xD/e5eJlDl88bFkJYyA0fl77Iaj/VnQtWQ9ubrxLyh9BB2vCKvYoJCH7RdsX20GoM92VrBNJTb8+mJWXsCIjHpLtfkh94QyN5AIbJKtKG9sf7Uj4Z+MP6zgHz/yk6sX8AIvN+y6wyMV+6SBDVmVvMqrwF4LoSfYi5mslKPwUafD/JMeyL+INJM2Qq1yfUo2t/fgb4IlY9gZed6lG3HnBH4ccoz1MaaVscCIW/HNqfqqDKGeeyp/hqs38nqY6lDVh+N9XigbeJ8h31zVgoQF9H3HjwaWua9BTdjJO63THxkIE2bs3dSwz8jQg0jeMPsnbRlKTR/kzoCNikTs/D0gOCgIYULW+q8sOESeKdU4PzrWJwewHkhHaB69rRgqkWmkk98YbRtCrBwxqslOZ+xlnzGWvKZektsSFy1hpiyJM9HRYYzmvS8/CGsDWm3mPoACBNMknbIQeh9UohktUmvEATe4RfwvSNAm4BI4V5NRXKbjNQXcwMNUBJ+ZFFjVnwzWfLDLoBGQ+qc0wWr6Bsu0JHBAat/+/XXXyXx2yKpULnOUyAMzWNQ5UAVfdNhfOoSQBbiB0Tta+bjAONr4nmcT/vvtfM+QZH8nUAUPv+B24/g9yM/YMBGr6RaxgB9wQYML2H4/+0P+m9GN2+DVsp7xtoyPHt8Cmo9xlokpRHY9ulQLSOXh7DtQ8ZapK5lWOv4AWklcFjLC6dQFC7SaGVhzHo0A+JfiZeJdhZa17P4fpCeZ35CmmXmdwCQf58O+dNCjp1Wy6Dk/oDOd6yjJZCLpIW0ItKTBU9MnDixsOkaqbDh2pQK8vBh+ECF6C5SZyCw6TTcvBYMRd6WKQ7frX55Hv1Fm0DKnHY8U96tvgdlt/286DliRnCcVJ+BCsnuRKnVa2ZiVZKagZUo5w4KEjyQLiq9V+q/5WLZMn8fQOYKVoekUC6VLV6si4S6mJoYaPIcFEX5JwrNGPz7EoJDxopgUBl3BICxoBZPKmKKHm+mmdJBmIQytsf4xgMVYTIdTi5Wu53VCQftuJZfoYdVZ/Ago1XTBRL+cRI5WaX6zLnwegfVb1N7s/pfeH3fnlCvqmfDG5up8Q71s1b1h07g0oNuov6dPcnnTyxF8ERNgEplwLdATgco//iB3AyT38E3ymDSo6BeXXoKGdxhdfpZ2oJqxllcZqAK6lr6NRZ+yfAr7YT6AFag/qCehSlqKv/PaB7QjAIhbb+cCb/I+jj4UD7nsDOp+07jYF6ycnxTSr5lQTHT1RdOG+krgfVzdLz9/TR+XVGHnCHeugfzSAQSJrxjsHEjNfdbYWYTv9Ws3Ca2zOcWAAosXoEm82f+FFg0UUrrV5WbW7/2K772JL12l/bambdbv9bwTavXluFrt6xAhRp0aJByZ0cy5jpGGft1KB54FNTWpSeDGjcoEs17v9YIyKe9d5/AGQLGo4ZyWrKD4sLXe0gRULdCKTDIZ2LURIldETJtvUYWRVAnup/A9XIHGKepGSybl8nwVsLtb6N4HqTRY5wGcvuB32AHFH7dBIIShbGU4yBR7Kw+TigTAe8pb+5DsWDGD74TWd2l8SdACpYCfZY5/INseKRSGfoNvnM8+yTZL5YD2nU8CKuWcQKdKJXqc6dDZDLvm1YEUYSJK1O/aUU8tx6D2rHftCKTe7B22DetyOQvWJv6TSsy+THWXvmNRiZHHfvLZNK3q4nRGt8CYE2U0wXdLEnqmlrmD9a5lbqq0eifQxQZPPwj+O6ZZQCDuAPccqd2B1D2IiNJsVpzEZHguOqr1eMOKA+PFOj/7FvMWrN0GbPkfGgKWYce4c/y6FnWy5plaASvn0L12T3FVUOteWxDqikn2Xj5bhXUxJOa2TXQ/2r+4u38YxdhsTQz3A1vsmdX8WfV8CxnYF+3mHFB/f0ES0H0K/xlNFEtpKoT6k8naF+30/b18WWE7+q/T5Cohwe3QkGeysmvWcTO9B5+ZnxVLi7T2ym18FuddUyvAPHQim/lf40WYNhrMK6RFfK2miK2t3KWM9l8jDJnmb7LfEsB2OqzlFTGYDNQ446RXNQ6nvYB7uAzBBni6WaKeh8XpYfTZi9nodhpdSz8Vi6DTicoj7HqRF6NBqt7sApIAyYmdsr1aI+Fpsl0+speKI5cTx+HbT+yEES5EtofX6PZlBk68KQZrOkVfq9NEdDYVmsyDTZRxoCLVhKGvz8qmHLyyeOQFS/5mc0A+vMtiSZi9MIbgIznl/GTCs1mA48vV75eppOPeQfMjKbVUnz1cma6xWBOKwygb2njs3H7UGioLG18xmsbA4MpOTDjrsLSxlcKgCh5bXjmjkwt5BtcQP7Fn9AIziTvgnUnOVuo5mmBleqvQrTr5/Y4mbhfjgg0eO9vUPavJHgEhgU9DVHinN86gNB7Bk8BnD61ofBYpFR4wCIJG8P9syUHsu+ySp6CJMlekX2m5ODL9vWCn8GVDff0tCqr/stMv76IFr2YYddT3VDa8AIgWwkFTdYGRgkw19jvqJF95yuPB0ZFQIX7O7NWc39gVCTVWLUaR2CUmWpitZqbA6MsVBOv1fTwFERRTRdWU/5KeyomcoBOrYhCqPLIyiSMFyOjJuL2FOXKrzinJLh9DePm88PzT/2AgiGMqziMxQVO263OQD/gvcwfC6LrczsEExp/WVzcVZ8zefdKThRW0rsY3vLG50zq/cMBOl+GvWVWsXv8Agabcmatw4+44Y1xAklF424hoTou6TCop08eQ7uaW66AtgU8ATTMCJphrlQT4LqX2/HGRTC76wBNbviC+y/LmS2PHBFMmtBarNB+QzdkZJSXc5PZIlJrxFWz0cXohe3/KKKl56ck5pEzxzCDGtn27HNpFmLuFmLPcZMOCSb/Ivqm089mug4PgGWkHQoMFQDkk+QyPxu3M2BOZPF7te856pvc4zdmPrkBJ3y33xwzwj83BqHvTFlvbxDdDU7RfQA0EIe9NrvCNb4E12mU07+cwIIrme5+soGA5V9Ks6iRDPE7lqLfBVPopBtMfkKEZtNbQ5OXGQiV574gSv16CkX9x71/UDDBaOx3+xfYSS5JqcCorLkOepzwEjwWV+UyMGXfIXlWE4iy5qUV1HQMy89wL7VcQC5ZzMT3JBo3LDRge3X2XsnPYI6R1LSUnjVsBTHTxUpmrfWzKuUbQqk9ovdhKxOIpisvLSVxbs0BgP0Cbi+dj39qJU+sjVYbe8U8D/4eq7cB6rK8CeOXMry9mvCW6Wn7lnI9LZwfP15liC/+mSLXu1zQ4xP+iX121e137ZdyPyNGn/O+66DvTz7l/knKlAfS2QT0wZFc5vgZ/53olOfanhHY0QXcEWzRIvgKUahWHZ1d2gdNF9gmIIaA6jkKpziR++ehJR4dhgaLbJMFZpIbpbz7GQtjPws1dV76iCD6+pLpNeH7/YaFFH1Po7mPL6boeyyG3sDuu4neKswfNtOWjPE60RSjdivwkR7UDwiZGM8FnUmF+6OItrxrZTpyur/LQkmukOwbxdwvO9BxDQw/8xVZDasteg/R3lrAV3wlVUPTCcqkpfy0wq522A5TEOLGzaN4NScF1YMoKqEZ0M92P8ii8GY/DLgO9EtUoj9hHcy7OYbOQLrtF6b+jr5HCQGYiDSF8rudi8JYjhyNSigalQCmhr/pvIuDDqv5biFLUlx2tUBTHCPZF1GbaaOB/WSNdPyiQI817eY7ZgdnFW8QZt3mlE9lCKeURZ8xTzH1F8TDG7KytcEhlOYvniOYHPZSpzhS0TqbWgif6ESf4O4ETEQjaM4O9XXK+cMYPSoQTmsQBX7x2/WSzIz+6sAGkCJf+Dc/+Cp6EzBBaEN70YvpWF3yvv/N7ktdynffvGht9zUvJlyeBON8CtTi9+o15lfkflKhgEROYUFQr+lGdqQ4B+rPIQL7FXwV6EwK0JkUTmckT0OkOO+NCET5SBB8SOAg8uWWjxoomEa5fvwE8fuVT/w9tm+BzUh5ZDyL2f6ex/dgC+zBa5bw/a1mBxnkSJ5DzDhbBxOZS4NPqxQ2SOM3ICQHB4PXmMRXd9QZBKp4BFKDIM4pgNrVmEj8rCT+UpBSRIJYyQG1fj3lHJDshZI4tFDzOKlv1DERchxty3Ik3KOUDz/RMapjC3deXplHJoWIT/RA3EgruXXiPn6focJCOlACUtR67CsStoJBmioiA5Y/bjconNJAEKZEzy8ovaJUtLIZdeCVhD0cRR/Gjof95Y6d8rGtTQ5h+2qGrtsBXY9xHBdf/x03NPvkBisKAYTyX37CxOpRyrdL+BRvf5WmiOsBoi9u7edhQTQcrOmglH7Eqeh30UgII4lC48mlsYvZEv4Jgh+WYxdznOxPhoLu4yKY+nFwjkD2+YtLuOCaQAGT0+PEVelxg2KyzIOSsuPFVcMFDJgblJR1DupquditvApfx0B50bsPDcNWQ7y4nx0rA/je/YdAZIr2pZ9hubx79gE0+4FoaXXKKzvOdyCrnwa7YGVHjJcCJOqYx+Om5EUdFzgMr3iKhuBrkrBVYsep3ZF9u/6BJ8oeAHzZCs+F2fuxpUNeFMCYe5f8ANLvoj0401sYu6t1eXwY6iQ4/G9jVBKpoFXMgfceNVxxOd740a/IG5V7PuSQj2jU+RfyxuIPNf6Fef1w4ovZcVbbpYdmw/Izxd27h/i/oPH/NXUa/5dAotmrXqjH43RplWl1JOIDXkR/TOGEtbuZMO/DbIAo4U0hERNd7KQz9kF7HnBColv+BAG+4++ei7F8wN89i7R5BMPmcWGRPg9Y23XxN6D9/d/0vS/ge6pQ13o0MwAb1NdhkP4ez29isYLQ/3Va/5jXTJd9x7F4olUcWLvUDxrooCGmBfBVIg8fa5sAaEbUa5+yGSdK4TXnGtBCwEiFf7StHwyhDgQEzLfE+hLlL4WQMxe6nJBWiTxOufIjzh2/o3W55HnTh3R+T6KNge2OYuo4b7uIEBfVkTohe5egy7dylTNwv9CL4XO1FVgKxfzhYxJx5aURiN9YjzgtL4ogfK5ib3gKhtBbQpFUzgMMLcOhd7fQIPnjwxBaXpSXQ0QxHuUaPpKaKsTWThytJU8OobU/h7CaE37Sz2dHhMYkCVw098ftgfdzfmKBdN4dpDwvpTbqNeeYMWb6z4yjnCInBuqzblui8sEHoPrHPEoSTSJIf/BsOjMlIjookxeh+R7AmYFE5c56Yn+whBGiF683QcblxfySrdcSBRlYT8X9AVsNQmCStfxztZ0UDdO2VYULy7MMm2U9bJbN5+i4mtr1DAZ94alC1X+6NcaWw0fUR5Dzv/yexvkXFCHbX1AYsxGDhjsAI/BUn/I0xIrehos4XKDPrWUB9RRMJCtZGfAeWkNKuARxo5lLEE0RqPKyPvxoV4l/7zIdSXJhuUA59DBvpx57Rkl/0oKanEExaMq/PsBNzcQ42ho+5TzjH9OV1xdq1rAnzmnxzjohwo4WCBjByeEl7ET6cgx23DjJPtM2QHyzyCVskasKqy0OudjP1EpHyh5nID2Ik5hzn0CU+y6X/0cSRAqb7vIcuMct7EbhtVCxSLOb9uHemXNXJLnPxuEpoQHqJyzcMHeHQEhDnv5J/u55Ne2UlneZENKtNYHIXsjZGJrKJ6mDoAtl67sMNRAMrddMHY4RVYHlGn/89F1Off6I0PkjZTsZ9B7vGFOBcDlROYpfA8l6oYlxBO+39cgsu2jMctUsFjy/5QPOLF+v/+vM8uF3NWb5N3hLza1HmbZemQbfVBdjP7AAAyS5RVxVJKXslVLK8slCZi+TxOG1tJrOwAih5MB39QWSRxGkJwtQLik5sAnKFvzprVxtYj6JIrdQBfIpu8Xi1QZcI/sFqVulVF+JgVsCrRIuDF9BN6xbSq3bXiDmFgqkuoy7R5yzCn+y1Rc4FsizMbaGltNgh1gImrNaegGRmolMUOfFuqfP4eZbbdayipMGxi/ImghAfyaC/In91kZw7QEBPRF1tgiu1nEC5rfYSgV4Mtc2OYIpbyjOKguZupZBhHrk2WCwjvWJCbvO4omEkyW4YFmYGGgv6j5W+UJNtMMzyGZENYXxmBvf1VIB+hPKtmGYDflWz2rY5AZeER/S5O268ufdTjSGyFJgWzhZWn1GJ0sDWbRR9i5t12fKx9Xba/n+JEqBF0mxvD8fAnqqL59BFCGQO2UvN2OEg74HfE+9uwnbHVWS34GXLqIMQPvtVjSty0X6Lj1mkQbjvnx+GWy8cWq0ztZT8WPx8DGH32wj2hWJrjWiXafxR2zWDre8v23ad88FhrrTC49FEfVxB/psY5FrBxrrd6vljdz+G/Ff8nGknSDz7+zj0ylhE5l+X3wnLAsHJTWZSHUJwa2Ys7wKpH53oN+H7BBTZVakv8/7sDlvoYjirA7+OGUr+Xl8fdDs9OQ2WgW/5RjUpu1xBwbFO8RVr6dTmphvkVvmuW2iFHAjuYq1iatyNMWrAq9Zc/mvACZn3zb1Nvj+C/h9/5vEgT1NwaxYeArPRM8cyqE7QfRiVMnZ+Z4CgT2ZtlGSqyR//zvhRWL7Dv+CV3NY1jYu1so7WWIwWKijVoxNuxOFCDKjljb+voHyn+TMtImAb1PxxcCoIZK4WrkLD3sxeXiHJEe55I9DcqvD/yrG1yPzb2aCxUlQEtWewVDqhOnhGa5C8mitJ8MEg4+W7MVi7gMsHGQ9vI2clDnJ/INsdGhzHO3eIX5z6kTAq8ls20I1fWIimuv9lqeArKBdT+n/NvGAiRW4TXQIB9He4rRNFLLjaz1PmwTyYWt5tCz3QuNh/j6pTF/d9gZjFTv0PJ5jQH9SJr/Fdu++ml94fhi1R9h5IOJDfsvFLbwzHhemeN7gHOLPFl0+zbKNwz4b3mB97lEL4VlJYeMrhS57oegZT1KS09bdHZhsm0LuPdxxqegfTkdLUhLsh0SkO8kuuQ4j9ICul5Y27nCj8eUUZSVzycczU7a47OVucXhDZsrFmq5a/pP5miTiW0hi135yGGLovrSAj0f05pqYLQk+XAQcSVz1HUZFKrexFqKPGWsPSxTB5p8bhbjksqtTc9xyHYpl3XHLJrnl9bip45G0JWMgzAB1KWPSJ9bAgqlOPLDe3+FBbB8A8tILbwKh+P4ixt8Adcj6Nwp9wMZhimqoU/ymhBjZqmtgrF1JLrZvBH2/SL0DvsRWG+9Tq3V4aBMKTG75Byng69WEZnYGPN0lF7IPZaYYvxX2mXsCzlgh7Fs1b4byAQnivObESxxPdK7vfszuSq6nglAml6Y3yBweKzDLOAh2ngsRou8BsmFblmL2V/8KFji6kMXvcBLtZ3Gj8kry8ECj1AxmMWcphhYO4E/zyIC+gsX1jLWliqsWplOoz0rbV+yRgx650WxEQajePel5WbaB8IRFxObgoucxG5j4djEasxIF7CHLdkee17aMJ30S5wzvZjLl38XTPUxK24CWGNZWLkrZKI2vlDwt0Ayv32MPN6eslxayfBMgLcjMK0A9aC9jBTVCKwrl0eMRERllWns6T4GCJ8GhUImULGgnknqZTNWYDwf5SATfApSAlH4PaQAlMKuLd09WfGZg5u3BtEq33CDV17lSdraWiEkSdsstymPzWTI/dgKjKw9/A56IuT6X2pZTviBYz3VR3JmRLjCfSA7P1wBVOBrlfABoYyQxrwv1C8isI+Vvqb//4KcflCRJ9QekJ+fSO+mYDrnwmFkKmDsyT5xfX32KSQ6soLNKsCIVRFLy8MwXFtlxwDxm5cjRT4LBkzF0yC9HPy9WnqMf1wJsGUXIw5FIXshOQlnOb6TjS1lxOYNPb6RU56tt5KiKNTSvryhUroEZWrEObUBfm4juej+luPGlLEJN3kVHaSj2Ym8WswrNAXAAo62JmY/5Ame4hBL/GtY1Jl47ouyYy3IG7lcGzdVyBv6JOQNH8CGs5k6lmQLzTPFjsGts0wWS4/CPkvR6MFjzmcv/ssbrlVfmkeiHPaivX2TKH2IreXPLvLYG7rZK5eZ8t385mwSa1LlbjunSLFZeshcimZ6OhsaMtD1pG7DRYoOjK0kIObrIwQrjr+BGlCnsPCmI3FAYpbVayM1ZhEmat02z4mLFOBOLYRqkfWOSNlhYzQE8LF/if1FCo7B6yz0bwlhjZQQzLFNDUE0GkDeDzdxt3ym+VeDAZsPSEKwePHLnxqQn3BHyA1UA8BANXAFnTJS0VZW2Kr469gh263qgmt2g+hhVk/IA3YIKiHbDAk+tYC0SvXihWZnTZgeZ9RyI0nkLbF+aGGlKx6DtZFyfAQJz9eFIYVjt2CrlMfVe9D2NZ3eZPR9EmA87ssWpYPnmpN5eek/iUZaEpRMxDMC+iNZG9NzbFW2mXqIlYi4LEWClsLXUOgBQSXwdqdx7AQsaiuQrxqgat/h9Xo6ufebI9b13HYJsDYHMaJ+zfFcetjKDkkAKE1fNeY/K+KExtAGvxcMbfsoW2AUzvqQUSQMXEFKJnmHkfe/xRDluL/YJv4dUKg+LB2Dsb7WQw3B+PV0aVYGQqiLMqcZw814gUZsmOuQFw0yj0Lw5twzPz7rkRfB3MXx4KaGamIsnbJx4YiFVMHhjPQzbBbQBIYgwxy2OnsAFAMZ1FN8scMQU4pGL+WwNGzi2V4UheWijURriumYWPJqO0WzJoDplykeQ/FNSHDtTDUVPIrH2s27SFfh3UXFE8KPF5usofWvTgqxawMe/iKGY4aueMwIiiMRGbC0CvGwg9EoFtQYgmsoceOMsBtTzbTMzYNRy13QVjeqPzmzVsdbdmwXJ4KJUsJf+HoMZJxdwlrqGeDdUfyoaBqaNxIO1IPOC/kz86KUkdlFfej8GQwJ0QErCjxOwcz+/HhnOy9PnUv/A0ErPZzmqS5t3FuB714vI686K+Q2SvV7M7UJWQzXJc1LISkir1PJcFwklB6afXW/fkX3urLimAOWNAZSXBMMbFkrCelw2bUvQX9hzxi3hFlhSI/xbxWlnknFPwvyYG/9iNANCFdvLD5N1bhEH6CIOUIyKSvfWiT5kvpxgoWT6Icck4mOegkiMPk0Wc9egWAU/08Xc7yLJZXoHwPezSHaCJdWUNUmctzCSfXcx++7vaYQwIBsTW1fsc/4PvLs3PwM0EARlMdfOhLt3iw304PdeIXoAn9PzZln+XRxGD57u3jY9uLL95enBOyy06KFiAz3IIXrAdzyd0wIdTBKHFctFE2dvNOVIAxmoxQyQ/A8gPQANkhEE74NIEDQni0v27kDCoNFAVjYSiJfxjK4HWBXlBR2HP6cIsFNQ/DRlO7RlIgOOE/brIKmwOkKyV2CAZAZ6pu+4mixU+czuNKSMtCwg/uKqAvg1SF+aj7z/w9L4GUvUqZX7yQX6WhGBwvWyr9S2emZgUCcgUCgY9kbha3BeZzyfF9XRICPZx9qmiJ6z8QYm0IpRIJDU2y6EY+8Kk76FQ0jLroziTJU2cyxRLcBMPB3jvbMnvDSvge+axRoHO0q7mcEAUEd51/N/wNCUKre9Qcz9KFziMc5F7dBIQpZGMg10a6DIpj+Ab/gwJqtxU8+b3bmP4IU+ML+5YfRW3nhZKruxJ964I2R5QS+H6bkCc94fysSZ+SZmL5uufcsNUjitK0ibzOK4nDrB8JzlJkaQB/CvSiydEkgFKVWSfRPIbGXulIMsRIsLXO7AoEhtVcVVpjynrUtNKunPbrnRLZ8hJ+gp5QqfHvgmL7Ni/qLZmjn4Ktp4e9cZtjCeU/PyoTNIZcr1xMIWMYjoCh7nh1xp0FgLzoFklQVFWsgThjfFMnmoZ5FD3prhqxRlZyxPz/9AL2QqTE9z+3vduw6pQLkzby4fxHICiUveJTOW7ZYPiqs8Gr25riez6pNgYD81bSSSfIleOMdJtxu0CkTZmnbzpcB0AVt1dcvH5L2UDzmlSbk+lyV63o8y4jgD/AGAbpgDIxOfdw0FQUnAG3EFxLwruuJ3g2KgA/4Q6jVxjEXpoFJyA+hjzS/0lAKjIvId3P9fmVJBsQDSQh4N4B6/G9+cRAD2oMZDqcE/6xkS8NIqEdslXXxeTkPFIeNbrvqzeCR2BdeTtJVabDKwebkW+tDRv1iX3wHHxG+LQbmUBs7lO39o59DZWzxzi47TARyWigFj0/bU9MM4jZQGSS7iQo6yI4c7BrZ3oBQ8AoIdCTbxeU8v0SgBdIlERpBKT5o6ET6O+CWMpRR3Zu1pZezlU990yRdxlRn2bctMOUcJa3B0kUtpWUJ5+Ja9wlF9d4eQFakOd4WQy+MNMT2in72P68429RQciVzkCpijcNPSbsNwWjYKtROGB+i83+dtz5BwABfxmADUmBwmwmnCLfQ+sR07yfulKSRu6eIlT5+oqV5oanukHQa6rOdGAnVGncEu2HONoHNLL9ePWS6P7V1MBi7XM5Kobxj99i3n3lDUKl32LaLnAtvJVmL63hN8n48RNOYtenYR8hEDRxPW8K2IGqRYgcLkwfM+7pQm0qHdeM4XXbeBhAWPC0BGTimDXiFNGm0O0zmG4qRrRP3+nOKsR11CuVG/blGef1nTr/+YGaZf32LUr7WARU3JxkVtMIX064JZqF/rQhcsNQFLjnTJ5fr9MxMoHyLQR7Xj2WBwPsC3cPXl4Lu2sxG+/4gIYSkD7pYI9hkG3H2ipyUMuLVtAPcPA3B3A3C3hQF3bdvAvX0CA+6+mZcAl+I7Oxn0tzbh23WmBt+ZL/3v4LvYAN9xr4TDlxtr0BrfCr5lsBJq4XmCL/r2Xf45eU4GK7I6BPpFSim7JPsOEKYK1Z8M58WwVwavrkg1CPKegc3MB0xWLL8l9SdYsEQed7HsRb7/uzbrcR1oRL7uJS2uo/mi0T5uWGI/ix13y0k8/iVM8rmPQ5h/9Od8/ChmhmXxore+aLzHi33z2xd5PBlSFBy6+uxF3S/9P8Oh8ByTvv7K+LL6GcZ2DY2N+Q0+mHHpuK7QxqX1oI2PzdTebIQ/N9D5O4bgnxgO/xU/GuDfewaH/9mLYfD/ZIYG/91G+JMiw4FzHwbN+h6M4FLkOVRAhIOaRgeqURfYRNOvZPAycfV5PrflMSlrOecRXGxbxQ02dNKPxPOeFTIj0CHF+GyCibQQJPnzdbOtnUkYYu4PgoFG6yHdqw0GOQed0g3p3ZtqGa9AZdkqzulmYWiWR0fUwgTWwJSGy6mleACyNz82az8jeq7uGNLE8awszkuNQFiltEgBB2jV3ISR+9AVFFGhfgvDuDtgbrZymZfs7rnvoGw72tZFFykB+hTF2ZtbN/w9Cv4jEEiZQDTZlpSRdgKlWxJoA1OsBmFsY8+QnO2yl0wbgUJBlg0UvqPulAMo+/88nYsGPa8wmhDeLsr0nUgX3y5LTzoj+ko7ssx1mJkOE5V7yqyYcPwdHBwTSE+5eShdWh0Oja06HpjqhcAOPF7Frh4JxWFri6NefYq7/Yr5gc+Pm3lspwGDpK2T0XzTCo0EygcywIgt3j/FMEVjdyeGbkyx4BqqZ2s3hsO+b65j8GGyP8MxozbDbRPqrLPMY0BBSilll0eKQqn3XI4Up0XPrS2Ue55bzDTVxa0ZAVMKJeG0JO91p+wAuaYdvAJKRbHLXiR6ziWhmQK2W00SHg38z1IBVBrQ6NZ2oMNC3l18i2N/6p0n2VHDSYI455qumkOkEiXZ0bZJKRUgZHKnCfeAIIDwL2yGdXjo9dgRjIpirMUtBzNlFYWgARzW4wyWMAkz/xSIee0xCEtezkXQTS65gXTk+ZxkM30kh3kDVhLDxWt0PIvOMgMiey4zv9su0ePFehD7UjbCZgI2uwO0edHzDJ1A5X6AlCLNDwB0Wd4ObLZirGBCrYRwAhCaL5YyKRs6W6iJhjWgqrJfojcKgOMSStAKS4R5DZ/xEWVpFuO425R2WRrHrcJQA19lgu64aJvrtvIaHHseuO6HOs4Z9eEWFQgolzJ16bK1HfKfF1gUVsgIKR802iF7nWHbo9ZgVsZODVZt3YLNrdTTvr1E19Z17Htq+f5fVMswirIJLDyl56PU7WnBY+zDRsQ3Ekt9D/A+7jkRpv2rA0/gBR0fYQpB4BUDYXPuaMcAQOLJQIYmoqegXUgMQ9HLj2sf4qWaHUj0dYjHBruk3m7bKLT5T5HkTaL3a9QKMapBc2wydQxbSZgRqDPl/cEMbGWoZ4GOBZvWzlwRoiezHcUZDRJEb2Y7g0UwIAnoohDWIx2ncea278EO2nm7tTNKke3bMRiw1xJ6P8xzwZF8qCvRMjPHKGumsn1E9GGhZvuv6Yo4S/zNG6AzDxrxX8BtoCupzBFYOfIcw94Nivs5DXu3EfaOjAnH3v/J59UHsL9mYUiqseKnCPBRKEHfFkdz1g6Zrw+Jy6lSwCxLQoEbs8rc1oUZbrzNnZE5HA2JRgPaEI3SDLKK+VuSVdopnimXykXBKbq8toaJJDtqOJ4imcAOQffUdc6OKF8NnKLlfY9spW++MY3rm6L3GXwm1LahWOpKcu4e2h8NqN4rzC+J12UakB53XM3fdTssV4D15rsRE5n009DGm6jp44em9dC072mdpYFrGOHy1EVo91Uhwn1DxkNL3tcGc/A0K/PWNhjci5nyb5oTDykIxUfJa7j1RpNzLc99jcr9/A9YaJjvHAZGrfK0Mhd7PxE0oVjye5hQvEYTiqOllEYuFEv+hJ6YyteuoFVZRRYHE2NW5fVcXm0whfhJOLfxU44sZlwOuUglcVihZmS2zw0ZmTe6PIWakVn23k82ZrbxWTKTRRXMzKy587CMZmbNflRqZhHHEteOUsOMBS7RoPNrVtkhJ7VzY7ltKaCYE9ZtX877R4z3k+/TV5D9vE7ouHYv2TdPc2hkI+v2MMVTmXaDG++bMGr0hEX2HWIuJkucGK6/RQEVUdNaSH/TLrv8L/oZXshn2HPzlwEf9Sex/dL+ab5f3KG4+zqM4st9mkemqrcEjf23of8ks02uz/1upHC0X09oefNxq1WYjPtjFyJU2JbziM1MWqDDUu2bMb7HMOxdX7FhM/3u/smMXiwwjnnzZDbm/eqLQXYOXreDxxTDcsWGApBBPGGeAi5TLT2ObFgfnDqMEmVtRdIQSHhwNCWDSDlNlF2pn8yO5eDyusdXG/V9HHrNFYb7XFJKsp5Acq6p5MlGOeSA0p2NeMZOJfdfRjnkf9b8Fxo0/4nPABX/Ny6Iwvcc0/wFjTGpJRy06UQLGhAs2DQzpdYtFOK4WFTnbpBeA0P1TbaGOXLkucyBQ38XQ//vzOdnVfJsEYatK3swjqTMg1GnAmUEEdhpFVi9s18IeowHEHz9PLL/qXC6j2c+ov+l0/0WWADliaeZTpFWYFAogJJoxCVMfmV0Rv0c/Sky42VOP4u9QeEWt3VN54mh85/8+92Aemm84qjy+NOaxX76n7Dwvj0aW0R8EKUqzbeVGehztR7H4+/RFSapvqQyuWkS27fhCe5QjQTFigFY/HEBUTEoIQUUdrjt67P/1N4l9zoUihnsOUW6oLQyQrCl879De69S9JZz2yXbmla+NeewrSn6YtoxGzJtz5OY54I7/Ejs1NzgJI5yDcDg6EZ59O2joXfUX/cZOjDKr4YO1PF4HXz97hCavEXJo0qbDR29ddA4rXApxPtqpOlSaws+CrOy/PSZZgFqp/SfdKk08d2k1tafJ/axA0k5PFSG7thRt5yh9DlT3wYae8ce47Dm8nkykhJSgGSr7qxsj8JkhOjdHMOGPIkAMtY2itKrolIm/Tc3oB7no16/j0bLY1w5UceoGH+UFOiSIwmVmfb1ouciXdKz2Q06KvAKz12UA6ILM1GouDe3ngTGiZYLEooNytYmslUUue0bRc+RBgpzxKOcdi9nGpUNjGkQpD7T5RH/fArfsjNTiOi5mc4QLiDiLno+hJfUx+sxCm5LWp2aWB3SWgHOK7j/8QXc3wHLuE/pDDjW+tNj6yu+NGNudrruW7b88DZspcx9jGqFxUjk3hZpiArQowFu6Xypas8sQZrpQdPuDQq/+u1eQBSU/7Pbg5JiB8FnQxwLl8JoYrVoP9PgDMqWGou3gLYGw++RDAws6KDDnwCGu7CdXMXtZHjDY2v7WFqlZtpA8pXOw+J8fwIrCpnDfmjXRpxI7rzYNnTJ3DfiQ7NVYzA1CyWVKJN6c+lLqMPGZHnyXHMSF/0Sg468I9ygM3qvMd/N/6wMeMq5HpdyRkLLhoAhUgFzDCHdSmy+9ZhbrkaNkqFkBV5QT16Wd8hIsp4M8Zv2YH6qo66Ucrd9DUfJH6FOzQqPh0KS5zKHaJpGJxBBmDMvMaSCEKXM4aTQW3s+TCyaQSmHm93yJpSrWYBbEtASdTzPmCFxmZpoCnKJv0/QPFjcbQw6nwtkh3fPM6pxKb0yqj4xS7jqkzf+UmJlntCaWO3ZG7IDaPhdxs84h8LNwtT0MJPWzlMhM5uGI1o/be2M5/dwQ0G6+S/odEZCnPrvECFe/s9L55Y8vrVat3fXpXPTjXqtJyl60YSoRuN8kOa9zS8bDTTxrSx6c+nISS275lXT37vH0clJFKpgl+U91sRWH0k6nQpS76zVDRgEgbvw0sn5uMMQyabgtZOFB8yar1u38glF0sA87GVqnGRfwfyocXT1bkE8ZqXZr/avQtmSTysULoChr/dEta7yzYk0+LGsRkWFqRnN0WQS9F0VHc5DfprArjvUTjjN0e+AYG44POk0j9JSPDJfYFl68IzTXAqu4KvHD0t4bV5qeAc0lNmpciViAoF53jl25UXvj40uYu/P5tBhVy0wAaS3TNSsVzIlWw9mOIL7q4DvUc1PjhtLtZM4cTYUvAeNnZoFzclNaGoq3aFaCN1LXOqT7I2iZ1IcM4yhRb6mi6aXg8oo2beI3g/am0x3CNmnJM9JIVuVAg4hFJqm75FJuGyBLpRtTT2AR4F5hKusWd9VjUyGEUncJu14bA7RgcAMwdBtx10h4RutAfImNAgIharnXBusZFOUMWfNRjE3ajczRodFJiEM17eSIihCKRSd5IgpVPftYEexE41J+gjbj1SEUb+XPjRSv0k69at57HLU7x9/N1C/SSHq99F5NltS9+RN6keUNNFM+XnVpCbjnhp4iu0pt6Z3czsX7akVbE+57TlsTzlqjXvKdCrEvdTPL4YBWKP9HMo90KwsLNe18QJD6J+GlQa4zkYrtnrgDyadYpfqYS4GjuFGES1QRGPLeJoBhCd+7lEqSqukvH31TN1jOxL1zeF4PgGlOGR3uZ/iBpY3SyjHVZxn4V9sjG5bshS4P5KSsVDo0bBNkn2rmPsVthJqpa0KMPWwcw61dDcv08swsGQXnoGtr8qUP8N7THBMUv0u4NAS5lRfL4mZxS55znwnF04z8K7fmez0AFtJJuLiwylhQivlxg6lYYItqs783ei/5QtNPDy56lIe3gXq1D9qtPgJXVCYVqoLCT/D08sLCR/i05T1NR8amNn8tpjZf4vLNpL5MZV0YHMOcxZ+xzLoIKEUstpr0y4DfZYWQ0Mb7VsBZ2IULQeGjGqmfqfNrn5v2PNuuYCj4pvkHYv9D40Fc+7/dpYxr9KzGvPyTTfoj7Q64RMIWwzSKbhmeA6v77XMek3ASznTKonAO4izOS7LE/j+91tGwWsTnZxDUGojL7MS57Ey4xNK86OMCbgaCWYEJdjGnPRxSKm9G5nDlfvkVgt/JfhvpJkH/620hPkZ1LM7Q9JUiGMkthET4Hs+mnn/NEEw9OQ/egSvmFfewIbH43fviWSEB+HBwkRfeJidJU1F+zsCAPPo7xG9H+OLa/VAScxJ9+SaUKQk7rgjFC8pNGmxGViZ0gC7TvT8A99O2UZsGnB9oDT4VQC6+KoL6/FUEntZ3qre3hAKTXehCTrkDbqiyqiQxqMcUN3C2ENIXy43h8vBYRBjhn03lzvwERtRq11Cctk39SG5TNtmRheQ5vp56TBlfW1o9Vy9ZauR2t+5TZOgdMmppnvr+3sZgRe9HbExl6uO4SQYO1yIfU/dFXacYIB2ekA79cFYX+B3bjiTs2yD0Nc8Tsw9s42lWp0kbV3KSTcj4eij1aKSmLUWswGtpysEyEzImmE0scu+W/SUmXSvFkZcsVhCeTO6YDekFaRslDwtEXgMOREv/hlfiZ8hK4M4tEgSGjDlEyPfvg2oSblTdiDbEr8tA+kjnT0RKoH548UVFZQW1smNhhm+4HQ3nsYPJBTcRWkAgDuU8duHCiW8ukF5aAziz0mnHJTGVygzMLpEWBQeFKT5ueQozjU0TkFsQw9EJr6xB/mGvDsUnVyFrUIsRD9lpL5VyVAxtJX6PPR/OcjGUFGdeJF1d4lB+5aLYbLLugWCvoP9A5QxzwKLES9eirr/hRMQuo749VJt/w6oc/nnhYFoI1qzRGkrAhy5KqxUEcBjvUuep7NUzk8X6YLCCv7RS1nSWKDoujSn239+C9FUIgSZwA6hu/kmo3Ne87xjTDIXopFKnN72X+Row4x1kfrPXykDfyzbqXlDTrCPJ4ZiHJKFkJtT7XKQRONYFpaeZ4XmNVvaIBDqxY2Xd26r92xjMg/xBS6MYxi77/gfmHdK3f0b5eTV7A0VIQlsAKDJ2yYjdQv0i5fQuLFPzKUr0DF295jJQAbbYhjZT6KQzpaIEUGZOQfU/5yhHaRHzD8++v8BjQ/8FoatHd8Mw9avJqNRI8ikBZoLOtdOT7sZ+uhEsiEdst6qauQ6JBSBHDe8EGWn8Wi500CBvOYQpV+WUor5tDgzsi/iG2g7PFeRcYT8cg2a3VazZ2fKteoXWzGlhDrgBFsp7F/9EvkNXy7VsYf7WULzS3sDlEamEZB548v7uIVdmzRpEPI+Jel+LTcYn5nmutfYT9fTYSaLNqU89fhmlqcNHSH+HjmzBf1gbU0Hpe993Lt1Zx0jJVivfb/gfi3rU5Iez0vI5gmaZ0W1mR+YHdPW8gNH6Ie0HxiNVOLleEMi4CGsSssNDJSZD0tJZk+S9MZlSsJohiJEHMYX68c/nyzQkvKRoS/SsvJ1RB5+bUOedt6bhcyzU+DyGk4T8tl5b+599OcN4E/ZeW/KIIz4zmwZK/Bcd7o3mJ63xraONRjCT32PEVfl4Qlwh/h2KT5eyx4bjn5L3BeWN9e2Bo9b5c20jQTK8gvxczzQnXalfu6buSu009vJrY9+j7jykqPf6fyQZEXro98VYUe/Cw1Hvwu19sry2Vy4Mhz5Rt0Jj3xTTpthZbpBRy6k09+GRIDVjJRk9cjwnshKlALuVLrKj6JIUrZqx6jbSpBUrSdIuvs+trTrtQRJ3pe7sYQv1QLnkpgTU3ICEM2IHo0jOa3BHBeM3ijh9AaITbVGbID2GM5/T9HD9P0r2PlvOvBd2jzLS69IgXztPHgDp3fElwIrKMsHNsMUi/QjSfuRHtHqjDi3SBnOiPMoA93XLefxg+F/zGUHw2MH9vhzLl7dckAkiuqUazVRC1O4LKbj4Zqtkx0TN2nHxBfyY+KUn0tzYVa55aN0RvzH23jAjTJuJDsl3p7OQxRnjXcJJSg2mfWD4iARKV+NYB7XP5X4EZrHdRd6XPs5YRYLw1yuGC2zkNlFF3HXq9I0CpjdF7q8auDkGbj0/TvBNKHSqR+Q4sKR1Cqn8ULD7y9MocaTtB/TtR+jOFfNN7whGc5fjTIc6KZDzqvmaPGgD6JTJJK5CTAHiH8VQtXln5NDzss5PHnbTX50zr6WwxI9aR4WRpRdnsYgbP0i5LraiSN/vMsfhS3fKnD0LOJSFuqFVxMD2ikuKHAmVcCW5I9EX5dohjhIpZ2BccBUODHGQSPj+DnIrl8uZzyexy7l8anhmuZo9ynDd70L8DdLowzj/+g1pIoL7sgh4aj/61DM9C+6k+Zq3zbtKWfKbvTa4cbIEFctisRLYhz2bbPudfnX3Il47bQfI01ZHFmFGTLxJvD+gDl5ZAZbRCOyN8GTKnHETszVO4Y5tPB5eD5ytHv4HgoyxprDJW6cNB5MPhGFJ64qRd+6jgyu+ZgvizItic6GtIKa9vMl+46psTxjT7y9YeYpl58tyQLkyIFvMJFOrcMzB/8K2rO57CDoFzLLi4O7ELmHYw0p/4TJoeTEpY2wpXG/+c15qKXy/MNLbUvZj5W25UzzpzaW218kE/AXSJmCmZSUJVUOOx30k40sJp8x+8mqK2iAT6PBpH+UjNm3mg32IXvx1CvkXSmF8npPtQgCfUk12bT744UYCwhQbllx5JtyUP5S9RARzHgoMGsuc4tjwhV5OaE+mi2GoxsdUKkcfeXs72LosDNmOCz3vmoahb2YcuQF8DMJs4g5uQl1FCU/KgF4y6zS4Tkk6opk7sFOJtPd8txD1UaDguZA8i0j11z/JEAD9dWL/N4lzrkD3X2amqGwk8fpXMydwsA7hi0o4iizz9RmioUPYML2AgADpa/lUjS6tvIIMuwwqpuHfdTETpyv3ONqnc99vsDss4UuzT7rYZgcdPyEqJaPybYQeGh2dgCzdAXm5TiZKXQ6PxuZw8GDr6FKKe/i+w+w0mX/fepg2HSNc8KzT1ld/q7wbFpP9ld8q8gRsxPk1wACT0NpbFCMXk8rSZgHAIUp/plfpL19jqAH94O87rXmURbJRQQ8O9t3WX2h4fI5AmuACQQF6Ume/RnJQaTldfYwZyFlVuWJrfw9JKge6l/wTg5PciEzpJIrKBUWB6qeB7PK7Y/HbKzLI/HWvtVn7srEYCzBwu5z9BlC8XZ2YqElo7h8Pydse4zsbrC0xJu4AdlS49NONcHsEPEAUsMLf0IWA7+GFHoUwW0/Jnrwwj7MfeVBmbX1xpk2Rber8Yi0HzE5pH05R9/DYltoO1FkBsBEYyoX+75pHXJYDCNM6XyUFmr2wT2gKVwfDNlrFdQ1BgeD0aYXclUpdH6GEetaD5Ell71EzP09jsHDp5ElhvvsYKZOhkKUSaNGfnOilmF9EaNK8DeMKC3JFvRdwImTzBQw5REX0ai5Xn0R/OyJht7EFuNCJCu7e2jsyQIoO92aw84jWe71CiZt7Pwr2red/j6JPB6tOKP1PlxI+/CU8rfhfB+2GkjNq0AvnIExQWJ9aQXA/CTODDPSDunskTV2yOsvwxljeNw28sWsKdKT6zlPfI3SZS1ox3hiwkseTE28pp2Jcehpw1KafJWvpLv8c9sxBnggQy5l7O8ApkS/3s92P6wJcb+N4sgGccRWeY2R902c77ZXZXskzuu0mYG0LHr3tKMzODRk0XtlB3K+Grax6G1Cw+d4rtPzcXNyKUXGbczF1PTVEVg1hcSXze7AbMrmX9qk36NT6+Ks5gNorkbUwyIcg2Lc2FyB6CWOkhEAJ6gu2E9gCMvbjJs80L2jO9APFr0mlvfH6VRXCm4bDmgyGKlltuL0f0LJc/2WW3LxtouLONraIR7vAM6JKYV+nrcHtbk6l6G80fz+XxB+iN+8mGzuSzVjexi2r5waYsEzh1Hq469nh+Vkd/Uw4LMNhrXczofFJvIK3YmsXhPU4YbxDrMxBZ1tMTuXFjm0bfw9qrzn1P18cf3hnZqPKfW4KWQszcQrYJsxtC3gjCR3yNZjGd4gHVvW9BFQREjx4FlNOW/x81qyOLKbALLwFjpm8ytnK8/8SuRoqcHsQBvc8lZJdBZnpO3RM8/yeDxJSy/F8SiHabNA0XIpHNxtG+CSN+I1rm666s7N7ebOvLG2EdqJVKTliVybWcyDcyTOGDXPghaVzxJaFLhAD7UXkoDuFocWoM7YE0AclYN7cH7eUH5o7GRfNO/scNlr3egL5AeMMrni6hadBWS4aga8uztgLrWa+DGask4MWaw8wpx2TEqZJDfpZ9IiR2Pivwo3DgTeWIA8iUV0CbX4IYUOi3WJluQzUkqTZK+Ace5w2xdQn6JnQifEtDun8Fwx+65lITKZndh0CaaBKUkumEXuNylamphfaMXKS89nDauGjrVMMfYupBSfdYr56132RjG3F54P8JxM8pwSsrqlVRrkZT1fzE6WL4ZnianVFxJIyArmpzlHSAxbfcUruLeLaiWx8B0CrX8N9w40iR5/HwxzKsKoVijmlsQaJqAdqYukm36dtgGUrfxMMtlg1M2xdN6QG9koLFv01DegC/O4K6XEZf8DFu0g6qgkjNmPip5d9LRaQwx+YEnTUVMaQD1NTGYpzIrT9bPBCzmCTiEZDjRV0ftxNzqoFKasKqZ0TVOdeJfxVLDom9KNJEpz6/jgRYb4YC5m4seUYUNAZ12iWwj9ndGUzsLeB/EgqMWC4dyr3zL5ZUHHd3/3haHz/Hvu5Ba1yPNhedrvv0s7T3rsHLNlYk/+QXloPr0ebZwxtcEg7TM3D2nBfTWK76tE2oSTMVPlb7r7XlYQnWmhQmiwOoKlytM3YcLimYKJ23IQJ3IJJwbymJrc1yKY0XAU8/LD9zPxllX2yQzvHtH3EWXKsqTMNMh0r3ZnqqlVCD/OOoqPW5OdyE75nUm/h8TOtAjR80S3cGFJnHPOZHCDcnGNAqp0ce3vsSFBirktT7QPRY277PXT0jURLes2l99sw5MDfbWTAyy0EwhsIj+untsdz6iG+9f4+W8HCUlPvBQmqWKCApe/i41LqRbpJU1EbVs2zRXZjcEkvZaDXtd4iV4XyzVhqxA6urya3R4fgiGTm5mm55RrU9bbK9DZL+/GzBUsUhplddL14kw5E2XvQ6ju+bWo+7k72bkPJl4hY4eV20kaoFegHPfed7nah5sijjRBrBqnaYLOwDgBxu2QS/UMM7nxifBiASrGTFdcRFMK89xcIlnv6mCkWL6jtJ79TS+iSz6oTjjJbNCEtvYs2wDRcz6aEtolCpmo7Fo+m2FAwVuvZKrfKJ6nJpGdh7Z8NyNs1W7EM47+rtqivTXjvy0aEMjXrAYsPdCVTP8GLPVbL8XSF6yIpWs4YBpjWmPpC+3YAjIsvSh6ulqJ9bKJeK1WHGEUpg/yYM4uN7AtRNgmQNidiLAIUNQYPXvxacoBPZJnX1qBS65gzs1Awm/XYojSn8r0gYBU7NgFI6VOW1JNLJBo0ftiNNLRUk5H3fIBt3xSyb9Do6NX3xFOR+/hF+MkhagoJ6sGYqoRUQEgVPOphrhaLG8GMGz5OoGFnqGs0c5LFvLs4SHjxbvznYaTM/Kr4Y7WAs3RCggvFKBr0V4liZnbJFl/b1xYvoyFdMoiRz9lsTh0yiLwgqBTcSP57qSfd7jKful5i3ftev6BlTxogGXZUU4MRM2k1ZVamvquIQGo8ag6qam1bLNrMYCaToUgyvuzJZS6Sj8pvIbrnoAYv/Dsbey5n91cwWeMJ4Y/xOcpmxBI9guEOBgq9GoLOzFMYpl+Ylg3Elewg8MLkhgPvsvODMSM597BDgdfaiHOG8DwZZdy8najhVj0RXdFCvVXrMS/A6bVLG2T486ubZPjNmWHc9zOLA/zv27n/Pbu2jB+e/B2jd+m1YYCD/mxrAbjsaxLydRLEYyikP/sj1Nhr/vf1Q6SVBtzTOlHirQDJa9qnZk7hpvIRhmdc+uP6+c1mS7mxFwJU+gsw+ozd+ENx4uBKnougMxZcywY5KZVdetpFqJDSf/FOUntww65L6D60Dn3dP1QJQ86EkRvBJ5z/+0wO+ChpVBNJ415F8vtfD0mJOE5ovSFwtg8/610wiIQ2wkPKY+iRftAYKdxaXYYsLZR9KyIIcdzCDi9+dlCjEqexiLdtQN9iKzjGJLqQLIXibnXxIegdrfs1aHYajElLipJlwRf69HsOS1totUn08LRSss33rk/xyupJQyv/P01vLoZ99bAFaQf5CbUGCN5OpzgkTxCUc2VE+e3Fb9Tc5zeZvE7bhYXPXW/+tuxNkfZPDV8lKH7+f7Vj4/znuZw/O+njfMW7basJKsRYTVqmXg5gL3ewdhskR6W1mpo/5wq0JDaKdW3GhzZkwyO5If6GRzZYStp93KmmYwXU61Wdf3bhYkgQATQ3UOZdlV8CyQB9TzdRsPOf6qPYByCUIhqz0wWjsYUGa70BfrdwXpBPSaBTuJkYRbLh0/jCZw6TWpiYq8mQ6DuvZh70iUeVnbuHMuH/1yIfTj9toU1HZSaWzj8b1AM9yZptoGX+cyrVCs/l7bYmEVPxuwhYfjB5M9ht+P5VZjofGhJ4mPh1IRLhMfsenYkE6dAZ4Q1xdwpb+jNZEl7IZ0VBhGGuQUG8vMx3rIObBjjhNDxKTpRPFEGiXCU7m2Q5JWFTHrk7hpyLMwtZP6DrgvowqTN8oLZKEDiGnn6xJFRjExSnnJBXjMHBcmQePQZ3iyL9YzM+WmRDUKjwKVhgQ2K+hx7FuARh/muUP4OsQrhnHG3rNRQcsuzeBK234oacb5yTxpfn+1ntfWR9+KFLkVp2vndn8+Gn9/9b4wiJNQdFgxMYuJZg533kvcHXPp+VkZo3HO1cV9B4+6TZzx/6U9lmyohNPZTShQf+36tSw1XWUKk+edD+4iFhTFwTT/fJrgWP0OfXVETP3G+clWqRk/OG+F1SnkzVYNX2vlL445S+TknjV4EYt+UhA2Sfa+Ya+/Mj+nXdzImZbwc3fGdvcpAb3h/TlnRNY2w2DCudeiSkJbbN+dsm0z/v3zWFNcGf7afNUJsjQaxZ54mBMvH/X8Th1dtczh+/fNmDV472F0N3Z4WmGKeE66AC4jcv51jcUKYZ/IX7qseJRgyEGG8XCKq5Yt5gBsdhnjbactEvmAlozje59FFA12InLnxBgmnzVrzLF7nzLIdKdtu5seXktpRVFlmYKQgBUYJlOPo2ixbZlYqFu8ODPrNxPNJklUtcia3o9VKQrlk5+EyuWuuRHny90x5i3vgTJtV9Iy6giCFt7Yakil06MIwj50iPwO6jMt+TsydEOQBxW5M48miRtwpdZJwVqJ7KQKDupFdDmTbFkkcSvlukM8OuoKdPbHyu2MlPFR1M6aikI/xk8o/p/Lr5h4BSUIZ3Jev1lHy8Vh8/zImFi3T1l+X0vXYoVBUthYeutgYCNz1bCgALEyY7XC6TX7e91/h/LyD8kkfLeVpuBx7VV+Njxej+pCyRfKUkZnR81kNi8YkdLFXTu2prmtmSBQmbxQJLjuACm/1uiMCz/ecovM9QwTNhKjm1xjon3a65/k6ZJEVRlUzkwx2T3Th8SQuGF1cX1Q1a41WO1zaGqsrpUzL48c0zTOYx29EHy2P38rel+Tx+6/WOsWgaC68Scvjlyi0Yqbl6sCTLIGMcRnVF06zUz7pWkhIhXbK5wKeHdK44ltFlDWXjsN5B7SjoDosYGZTOnNid9sGQCtYwO5PGiwRBR1DG9Yl75UXaHLDRLRH9Hwy/BIda5v+zguT/ptdApb7H4LBLnEULQ5yrcEuMUG41C4xivhnvZg7NLK1SeKTSKPh7LzoOWsymiQOm0KDJFNvrejZSjh5JtyWxkwT20XPD7Rlj+knOo6GmSZu6YQa5kHlzxsRXxSjaWIcIktp1sOSUKwjyzGgoUrPGzVkeTUlDFluRmFv3F8xSTwD+FbzZUjs0mJpI11yKZPzmby1A9BYvRfvsV7JxK2yqVfIpy8RuBa1UNjwTyhrodzSm4ko9s2SXOXmkeM8l5k4bDOTuDC57ECem8/7RwxKWRtMOTiDAZpMNdEhzx3GMoIzqc0lr6ErArQrA6CaZLHC/Vb/3A4oc8Ebc1DikrcW7r+m/VzmN6a6cQJm8sz9k+U5IoeeJKCfPi2G3LMkdHmcMFa6wxavGaAjbzkscNGU7bg7YMaLR1g6cfg0ZRtjycRRjDaLlORWyyXOLv7lucS9PKfOERbcPjI5LCr4i9ZRwZg9fLEhKtglVOIVd70xTo+nCq+IYQbgHDoDU4Ql4BOT8JrBKTnM0oRp/xNYkPcAzA8P8v3fEshlkYnHvNoS8TVxCR1ek9DRNUVzqYVfOMJ1D9QAziiXsSKktiHcpbdB8u94HGWGQQu5P/yH641yHbes3HQDl+sy5Xr1nothPIWMk66LbbKTvROYDgby7iPXcz5y9cUwPrLteo2PWDAEQr5wqcXBb3ke+qn1LE8k56g641TIXsVCltSbjhuqdDeqesVxBpw8IWyX4UgTyVyxt81h3zBBIJ1F44IYr/NBrzbyf15vyP9p1B/VZSfpqCsGm2oxSZ7fuMGGyXvWtuQ9VPEkFpzvnYSh3rbTWh6jNTwfGXe9cD+ILyjmvQVsUv3b8dBhIon7/jW9aViY3rSmjOlNa4x6UxnTm64gq/sC2sLQ2RQhpIyRznQGeqRwrNnhutNTGIBTJpQ5bSMEmb3HFUSgVIVoopdZEcZPNEtddIbuAce61uTM8zKagF47cvkGESoeFOHH7chBinm60DlI28yDefxRiiFV3Fxn3CDxugHMu/WsYT30pLupre1kt7b76+I+F3HV948Gg6QgPknW0TXh6qy8YHi4JlvehiZbHqbJtvAIOPWO02GzkXiwoz8aZ7QlwnSpdoePsh5sQ1lw/EPQ/RR+cz5XLWraKSuu5fYS7j/XtAflhuv021Q19wbHgFVZtkQPI+tCujXLNoJm38AzxbCmKlFCDXMZ4YN/J4P8InBHr+C9hNipp/e1uUfRKhcuqTb25BRm85kwCvPctRqF+c+ZkC3bHamR3C/o3PD5o6EDeiFyvLJNsVtdd/TyyNkM+Ka2qw87IE5xM57724VPjcSnXbjN7z7YRvPHMeMPniP/9jAFVWrw5WBcE8Y/dKCiK9a+Qcz9AjHPCMcphDmotTAX1o4ovNIpIxJtXV+QrnQ0mlm+WE6SzUAbc2baRgIbK97L8paOAVFhAp7Wn/cdrxkHNdFxPP3wEX49GsMNRU1iEEX2ug4DZkFafXJliLHW12O8QG+8V5HdZR8TFzJYqyP3srhMrs+7/LeRSh8wv0n5SlrE3GuiePLCWgvzTdk15ebpZiOljW+DEQ65ZD/IewGpbnqMbQmmUzGrsX9QvrJ2ALvYdxSP49Ce02YPYh5mJjwBYLmJqQ3ZaWUZS8LFtvlfkKEaoVOgtpr8BIowiVDvm3SBieMgo7vhlFajSerngI8oZ/0NYwFbj0objWYY44NCrWKAS2MLbYyQGc+0kfKRefqHkdrUEMT9bLgwQFyva6MuY28JqQGvWfQ5gjqHw+8Iw1f3kKFoLt+c2sk0ti4Yr7DjWkpQtG6soB9pCOXG4st5ScYiIVMwqeV/hJKerqHTMID3L6K/ZeBynnJ0coRB98BjlZpTIE/Ld7qWRTpcRRw8Owb1j9x/RTMbyXTjOQJ11/kQ88rEaCBDhItbP+uJBhJ2FtWJd6Rx+wk3piLxW2wKi7SZHI0mE1zraIobmwUsMmshv42B7ojMlM9purD62knK76CfxxulHUK7Br0EKcUhoxW6DdTdx8PyCclVEjBd+/ppa6RAv06YuED3opSJnq9wibcqoaNuouddrEqpqFnghq3WGxMvYNAkjTuaUrHWuuVG5pfr7bZNd9uVqda0Slf9eZYAFg/T1rnspaLnDEsSns/8RYuBzmUGMgTXVmVkwG2htJG0XrlyDIVoid7CMBXyh9BpFLdukuJbm9+iCOpEXgI5iRI6mvW0sKA5Kv/pzkzbYwwY5eYLo/kjx1fg7SeX6Vr55M5QD3raEdmKKUD1BWav6AjlW0N8tBUOcRBEiL65XJBhAnk8xgX41+iRbuSmbp3johzg2mZ6i3LQJqNCF8NQTFqfs0yI+YK7CJA/uAIPAOfYIonDtlCGC+vZy2W4qDJmuACtrJF50F3yR60zXDSwDBfl/HgyZpDW7llhLEpdcka/v4MjLotJoBCFF/Ba9PpG7hxUT5HBpVFKOS3ZC6dt0U9lVmKSg60q3f3ErWcGLF2JTwFLP/+/mtxQJ1vctshS8ZDARZUR3bio8sl5JrYbvVKF3bTjjT56mmflGfOZWHAHcumBaPDJTUIXLJcKrKNtI9TpeN023xqUGM0NCP9opH4KiXKjna9l50BD4oMLrWBtO5nUwI42bfPmhwQSj5iCv4NjN+iRK0CAfDaxDR3yWCLXITnyZ/jqgLS7uZrBib3oS4EFUM+iquSr0yz5tRp2u4HmBgatkoSgCwhV7ufkBA5mTYWO/qtXQ/S+eco4DUvGgwJJh9o+ZK4O2KtTWPCb8msqQZLCWPmARd8czJI36hTlNw2YeTIQIJj9qfO9UkqZy14veq4/hSbKevVJY/5Vucqdgjg+rVSCWQfMt7lTYBIFoicdbcxIKhsACcuJevbFqpTamiV0O3O5ZkxVfz9G6RpwnQSG5O2OG927kbt0967ETz9JAxdq6Xh4iquj50PpeHapFWG5sjL2GDrghvWB+VoHeayD58I66ET53po0a7fGvNIKWvOrTNj2Oke7lHn59mxHl+lWdeMBliCIHTRpCnHD8O4u7Us90xDCftH7KsZ4BjIFjSFMvd7DCLRJzPsXPHOwaILTjcyaQUJn3WHqgbfKaGCkOplGsj4zRVGLG3G2FcBb+2ynE9Z34/FRgUlk+fyKjFFi7hsnGMkMI8IB811EboeW6TmGtTtE5XKesaKQ26rI9lliMkojqyhG5qe7+E1Y5SnoXvYEBWn8BjSZpQMt5skphEYg8fzmYC1RxUmoapH+tTMqLDuFNtnpYwHxNJs6nq3lB51ccgEyw1JmLTU3m4zM8IsECiMMMT2l7HZDLi1QsFhq+GRO/jWSzyOomHHbwADkjXolUGRKVVEIEgBPViGPto1S7cf1rA56b/9DVgcNxurjx1l86xiW8P2Oi3we7BDqni6wt28KnZdBWV6dVt2mmy36PpYJYBJXDz7uA+/uP8hkU8btj+gpCA50DgbXKtzQ/YXAjPY88OTJNQZ1qA4TjKDhWf0O2FxapdpXaXNrsRO4/+PWUhdfxA0wXPjrO0jfjdnjdcuKUKj5YwDbb6I8b4UAvYtNYdD7sDNulXD5RZNy1IN1xl11K7LpTy+G5F/d37NzK160Evu1nmTJWs+SLJnqDRvb16GOS0PqW8fwq7hQXx1j+WEGpNWR2TRtAybzmKShMQZbjFMvbgF8zUtiAp734BGkdfuB1hXquUp43EsnZga35zOC916DRvDWZ/+uLjuC9P8BUDOaGw0ZBkLpBap5uqd02JuvxEj+YVYW6xQY/MQgwaRc25kug5fGs3tXMWq/HuNNn6zCoylufy95pABy66GsARniquU2dM/guRxfbxJIB1+HfezthLhW5M/BW6MDkiC/hj++uEv0XoylVs0DoVV+J0SAPt0zA7/Q7eH++ek886bvvJWOZtjG6RdM0yXkAU2WcWIilMk2Cbr6Hrt6GrrKyU9jagbbDQnqCMFUlpOmZ/OUiQ7QrPyDcn3BGbepz+uplJVH4rnI80/afoMfwW674jzGz+cHWxZCh/5B81cn8mAVugN+W0cmNqyVPA2Jos/GRa4cRpEOA8tfm8Rj+bShp2q3BJHexO9klAsxBxBQrTPxuLlgBPc2sM/Q/Q59cCSBwW6oU6Z04i7oBfGYZZCngShXkjshOk6Ps/M7qT2/mmk3B/rfTl0NvhbfPtARSVQ0GgNSeUa47h1Q+UoiWeFZ7hKQ3IEVGAkqrqKAUDwnXxuPknI0k9RBuULKyEVTHM2UFpaTJdXpH2sbhKIBHzymMpTUodHh903DJ9L2uANfYESmy3+Fy5+B3pKp4wDDbs5kGHYNjHmbHdZhXjyuAy2dwz/I6wuK8m3C5cbpqwVi5rkwXnz9BTMdvCoWQv1PW4xzBrz5jsXAyvP5ZQh5OSLzXCSz0EtJAEY0zY0qNB7okeSdkqdJyBropoFXYhhlmL/YvhOHGxuPjuPZ+9mFtZ41EhozTDP2sz7g1eRal1iYoaEBdJWTPzSD2OckMsXmsPEUiPKYFnbbtCT53yBGMnC0LVX0OCgcD1jSbliA77pStn66/ytO89C3EKZ8ADxOeVA04m/VPYS/uPJjCImVriJD3kKGvMtbGJUa5w4sZ9gaSLiujmOwWz6FGRVyQkiM6a4Ig522KTr63tqBMtzACN44j9inTBXZPMZhjMK6335l/1FgC16qpJ0bA9XKUyZI9UfxV+GxSBBB38wUCkAo9RSkSp7GGEnemjcs+MIODHzwbMPYGPk0KuUp+6XAvUD/mq4W53zfGfku8Ob60uZn4/KiUIg+5vJUV7tTyktbnk2vljxKEqxQUsnBl4cVCCUHXjYVljbPGlINimX2Xre9UPQuo55rnYC+KQV4raK8BV52B0YGXZ7GDuKcW+gTpzNTCksKX3zWUVtyYIbJcjV8qeTfM2Z5zQi19LpyUfQGydXf6PLsr3UKG90pIONscQcegm6aop5PyxQK3SmbS5teGdZAPfzBetjhjeU9RItelufkaIMAKmSDuGo6LOWZ9Lw1/djKTAkSJMgYump6S2AqCFp1hsct8Hjay/CoOTA1IvxRMz76Jzy6GJgaGf7oIj4aDo8uBKaawx9dwEd94FFTYKol/FETPuoorprSGBgSJS1Mz1tJgJDGF7oFpYwRocErz5JfSvlHHCHobCgqn8ZxUlYaTsoejSPOmnfnhWAQJNYpYm6/C4ws9q8+S7TsQXy9KzRTb75A8W0PIG2i2Ndv6OajXqrEqMhEaB3oD7tBitWpiCtg9jr9qaDjTR/O0hmQVzetcq3QKvmGnycxYN5xosWjaHCvdMCTkYzlD4IvkoCs3hjBjsbQ3q71kNdMYDfGBgZH4yiK2uN+SBgPoyvddeoQfmuFlga/cRYTdEobny8oy0nFzjWO1SUXTyvTMBZwr3xCtIRJUCqzOpSefn5DaeMz5lzApcF4d8qfwwX9eOgrzDjh0M4+L6A7C/zmXDoHvZJNDIdgjKcEWCJIAZ5TJzjEVVHeguyxBCIWPkAZaBCeAOcZ+C3UAbVIjWq6RnYus9r/yICU4dswvR0A7BtS/Wd8IWS/DCVUGYSst9COHhis3grQWdoOGTnO3JSVweeeVglSCIugTogdzqbclacw8s+NIEfYBtF3HxNAlmA3j0I3DICmtD3qh416XN8XQtYCXB8nFyn1uOVHrJx+RgQN8ag5PCftiRgtHvUgo7fwITt+6FxMaLx9Wo8XsE/0bSBRZnB7bF0Wow+LaULhByCgX7c/fwCBb2E/QsScdM0Zw5kpcqHnb81IOxTOf+4JmAfhrce9NM6TQZxHzFuM9l37gey9mfJFV2DsFUEnsPpBjtmHsOHsg/hvpn/unxQ2AeKVqZ3ZNLL33MPsbgiQudDVL9W6hLfR9ExKDkzmzltgMo1WRGSoYPyeQ8tNLAtIs07q3XJ+Mm3r+UkEzYWJdDYV6P+pSJ3+45lSTKlcf9TdBv0H0hvjAvrvAPov2TeLni3tmWaFJ1HPSIEXgf4Hgf4faI80F1SyDUT/TUj/612eA9WZKVs1SBmAZvhp4A7lrbjD8GqXvRC5A8iQd8QSq8qQt7pTKog77HSn7HQH/g5k/QJwh7/RADZlpmxD7jCUcQcMmSLu0CXEHWJIeb3g8hyszRB2uVOq3Cn73IFZ0E0w6vlbMoVt7pRdwB0cjDusNXHu0D3EHco5d3CANs3Yg2v8BqDJsYwmS0EC1L85e3AEXKiIG5630PPZ7HkzPI8If96MFws9jkwCnkWGP7uIz1zIJeCZOfzZBXzWF9kEPLOEP2vCZ8AnpEZHwAGMIm8u5xOVbuFMWQQR4XS3XKcE+jFJZEymP6vU5Mj5hYSkLJT3i24G3Hs5Khgc6l/wKfmh5neBZ6w0TpC3ovQVnCXnxZO0OPdDrPVtmBHLYwPmxzNi/CL20z8KpZUV4/heDLsIhttxB685DuThYhTebNj3uSEC8+kNQ4NoOxPL8l2ufA2PHZhbimZT5bD/Kc6LwdQjT+5BKqWWnuFxEhqHoe1vNhnu8uYKgnImiqXC3XGGUuEi8UwUvevJNZwQR98HRPzlArfrOGWlVlzxGtJe0YeX0/gTqhx4LrAO8z5wezye4gKimQZCYLGDJc7qNcTfPdW3R5RLzJicplRw2LdPw4C6JdDA5Skz473pe/w9Xoetjs22mDEN3susRHy5poNyfSQnmjddaEU05X3Ke5GanTj+gk5/16ZSInieDjEW77XcIAXYVSmYquKQpvGs648q/R4l0sIlhO8iaTWK+8KyvWImaOxMF0zlmr+BweX9SOQ1J0Svn47zbl3XHplPIANUaTVCqt+FzvDowBSrvUUcUu+w14q5eAgR+38C/g68EuQ2+FtXGCV6a7DiYbPoPWdFPThCnHOeaqyiNwJYjWc/PDpJNbGi9ymsaTCLcx6MwZp40TuUaiyi92aq6SJ621FNtOiro7dgVUvghyM/mpbxVEnhjGfWAxffs9ZKfPuZHUCBxmzAf/aklMuNUgD5+8tjKgvVyNLzLXHyBXJ6WiShsKYj6P9JULkRU1l7f4qC9w8/j4fpryjIOgQiwAagVfL6gd1zRe90eBhwCE48ha7Ap+Wygd2/F73jqTqCqiMFvdpN1ZFUfdykV/enajNVbw9VX03VFqpeG6qOpuooqv48VI1+8YAjmqrnh6p3UbUVqqe9zKvKqCoGq57iVT9QVTuseohXLaaq9ljl5FUBqorFqjRe9SJVxWHV1bzqCarqgFXt5cKB3V8TvaMxH8/4Hr47Cd+9vckeZFnVR4CVOgBSqPss5QsFhWdIBImzvXsDXh4RiErcA29J4xey8JALmrwQgy1KoEXanhDSUiQWnVEd2xAMAhe/wZ1yAHbtSkM6WWY3WEDylJPfB4pcfExNt9B5hw+CLSzWU/Q1sJ3y3o3wvdECErg6TQmUi/GetsEhO4ZyFt4j+wVy8TGkB3o/o3tPDqgb6oPBWs9ykrAEdTF6z5nU5fAvMGvH+ZKwkcOz3MxadaznsYtq9ikgRotoZzvkP9R0BOH4HrcOZhDd1QQU09MsiK8uRSKwR13fxGLZQd/9eT7GmnlOCejv8zxRqz2o3yXJfrrj6f5aTk+VT1paWDBQa/JzJZ/Yn/6E8kGCSU2EhVCyWWvRl9YGwVJaWjjB6nxB9+MZ5XgAqjMFgBrErgMslT0X08mi4gatGBPwn8Ipk9As+r6MYAkXWZoWxnqCydDJauiErhFihn4gZ6MG8eszXHKpUexfQ2K/JO8LSf5oPwMJnoRxSq++nInxiCLKChPJ5fsHtpLLh0eybC7M/4CeAdd47l23/D6QzrLM1+Xhe5o5pK69VB4+pfzJQVWlRpITCYfsSvnNPXAyxrftJNvMaJY7eDELStcROqUIQDoIDU6JGlJz/aMmMSSPKZsu8u//wOwZm24AmM3Bz2Lia8JmtFL6LUV3GLC5VzMbVwEzaLzQgnNcYOOTPAVNM+WTxusq0DaV6O8+v6ad8reLl8GkiosckzCJTDKM5S4cSxN8yi2f5sK/JBcB64jQLYwA/3/cwZOePBeB8u4h0Ts8giWiSb50G/m6RxBqHLoeuv4YuuZqAgYxJZtEb+cao3EtzLKGkE5WD9FJKhPtYjpTPPCi4eCc7BnAI9O/YMV0Fv9NFzN5+tG9iBfJLsise72dmnGQjHx0dSaL8ggMduAQLwJM+NRFL+YlDM37SbvQSgWKw9gYTBIE4jqmKhnc0gu6+Am6kBmR/JVM5mfUxvPBIJNuLciCGj37G5xCIbqs72rELI571O3n8G9lRtoGNQcPsY1/i69tZzsK+xOAhBlWF6nkKLa6LzVdZnXPNPHVRdCNcvuhCyKuMMyHcJidYJgEVWZLFtQDSLlyfuFz73cGUYyd/Yg8o9E+CS8jT+V33pCo0wh0HicSfx4nUKC2b0DRR32iIRhkS4pL6cJrbTZqq6vGn2HvTGsMI7Hbm0GLzKXvAzYbsIKwQd6oVp0OBtHysZuQDT42t5lo74+3M9r76HlOe33JjUR7Hziv+xun1ZPfcHQLv01dvbsFn5Fx46F6/EkTdNfrFg9sGUV3sGCoyyUDUp+iBJwb1IvH8W1q2QHftuCv480EjrRK9S0MkZYV9bcT2IweHgW0yDeb+J1+Dvazsk4D8opmBp634Q1PMGJWFLv+PTy1styCvg+XfE5zfyR11rMr1+PSB/rfcpQ4owvoUjyFgDht6cpAxJfBObcJJgHKWeK7XtsndBVOS6ToHdWbBdOie8gRGHYxMwBUJCMt6BRXraRmmYEJJUku/6OAaP03VRPxVtRG+tqtB6kIIueCAkdMuVIJ1VRweUqtjpiyTPvx7FJnHutHu08Tk4z9m+MtYjYxDuXzCy3ob19ioiyp2d34yZ5eplqTabApB0PI2NN1pmrMD43TRdcJydNlydywuw47VAY2socSPfw4md/rvA6zmqBzQLmjkT5GTi52CbzfMqI/UyZE7UjPAtZgnSkdz9WdUP4DL5U7bTZUdVDDSYqkS/DGUAZVuQx+jsVH5Szf/CV5bTXDmJa9HqqWalWh7Lb5pnjMa9X9ZrxtLkVxyc3AGTD7Bl4CI+9VUhtoh4t5p2xkxgZCDT9GBGwD0ja4PBdvFue8fAOqZMu+Yv8hGYnH9A04Jlf9IfQ0YeoXthL+lTyhGDtcIRUes5SxjM5kHhmgp9iteRHocQ5bNyAUU8348mhbVgZKTdtMzMGZjjb1JKL9Ccv3og60lqVNP4q+2SN1LUH0GKI3uwlmIRejZ2BBV3YUZTqF2k7XjqJQdPkA0ZN/bcgFVdr0Srw/3QwawDaHXMjT+rvkKgdTkmF0nzDn/egg3Q3Ix1oRaSJOAmPdk9W79TjjLhnnnTBO9f4gYzgs9++UeLd/XKJ/eiyG0c1n4WJLWO/3UhqvE2l7kEaNx8ywZJ+UW5w8xzhF6+5HtZDlHK0jdJdSdin96/lS9rsCR/1RN9yRzePFeUlX44jZ69oSYZLnvMFX0Ker2TRn2EKwcfrHxOIYM7DZ4ySySPHOgUDpxcDRK7EIMqdrfLFUWG1xB/pEOvwZsbg38uBZpj8z3iX8SpHMR7vhabH906Iz5cfjM+X9Gf4HrLjG804iIfBnmFzjd6PYTkOTeZha4UGzWygOyTuZA61i7tdEYI4Jmf5x1tKmZ++pzZAfsDo8TYI4bwN8tKSw8ZUtBIq0gpo7mZyWaR9rjZ8mSePPwDDNUuER6LbALZS5/Vdn2i9MGwzdRAVmdhJKm2aZHPYmcd5B8oIWSeO3BEabItDB7Ar0s0Jzh71y1nfYidwEXcDLU4vhJSvMTPR8RE78x+MlTw3OEAfrweV28jQzTh5955Y3ufwPJEqzD5pQaLdvE18/2iMEcYS2/luYYBtX2vhsepJ2G0Xp6WlV1pL9ja8Ulzb+vgEn+yt5JO/tBB8YONM2VgxsuwqgUNx47a+CI/CQkOELivM6dw+djK25OywnwP/mJ8CJYIR9emcBzrjGlzsD04MIEMdWDB10jd/C3PGnpYHdpm5B2DjknUAEXancJjTpIqpLOWYWBN8jDeu1O1llj5U7LMfBb4zTyEfC57CXO8QR5bKHvP4FWT3kIv2Yb+DnZHbcwoxb7KpzLdC5hzpXW0A/ITLyknYPNq6M+mNzKA+jXKsORsm58GCSE8SumOIQ2k+yOv3jYktbnkV0z7LZxMDDCcjHRlBGnXmrElh6gVE1GRP/Ovxano0obZmFf4ckwo/0ROzLG0CX8fgyZ2BK0LG1RfpXwQDX+B3SvyoHYCymcEYaeOXUUklOdMibnfKkeKc8rktp445RVuhASsxhERVAMMTuLA1SNbs/JZ/lbfc1NCEUYMT9utNXcMOOwm9IQpUWkun3cuXJaZsUonZVZqSCezTuivqLPVL0HcUV8Q+NdXhOChn+odZM/78SZeZMh+p4+LmA/ezCc/i7/EOTtMtS4HeydlcK/E7F33kGodvtH7UeyGIFwL7K6Zf+QPhXO/BygnmbOjNxAoVhvr+dcjHSCsLqDBjfSLtz4IBp90njt9IEAYJuocot7Hb7IzLtFdOGI/wDM2OE8DVw2FvEeTEW5okbHwy4TRGZ/woOuCfQZSC86LBvnvU5dic3QmfQzdSfHHKVk58aRuDggICRZrllEIymWGF9YI2kLrQ8eKFKXSRjhOH0vdZMmWa1PDumrCyK7ca74Bi88ZWFjM5r9+bxBFGM0HPC707ZrzhPc4L/SQwuXGw75tqfdyGOBTYr/PptljYUI8hB4cj7t1nvEXNEbRHo3OkYO6sSA4UY0D1eu8hqJgg9QOMpvIkF9PrTidI/1i50JboWJef2j4wH0eEmPECU+2EMJ/1u+QkkjFr0sdN/L2MB5+kNIXP8Aac8E4/pj7UluwoPmTOFknD/DdH/X3T6P8mK/gO3rdYp38s5wDvtGOBwxsQJ0goIWjWD0J810j45sW0+ACNtboMP9CZdtcg9fh/yARfwo3sC/RKheWs+0DyVEnMpRCSRH6iiZy+x/ifjXZ7jMG2V+MFQ4gc4SbwYSEvl6pq9H1lBpvyr5B+V6LJvfSVDwwL/Gn7v6wZyJ0opW5HO/XCiJai9rC+wPC6x1fl8DAnTdle+MYhRyLKNcwkleE6I0kR4hph19pHejiSiRfQGcpCS4v3AS4iPXJMIYAXmsxe32/8j/3gl+lL+UaXzj13SwDQj/4i5kfEP336W3e4TLi+yQ9EstpvBAVPu7oyihMdIiISxtilEZS10Nnk5kZkBFJeBx3zdRA45CGEcSVJMBZI5b7cLLMBaYVdYkWikdoxAwzmwlAEtGD+GK6s+EeInGgogXznfTLLiJ8xvx5eIi4ei958RXLLVBEQgZtoFroGE9SD4cuETV9tyPCTgdjvZEnTIpSjhJpgpqjls7hvEPDqApc2zFRB85iBL6/CJYVacWaibz2n2PCOBkys0GqdecSF0jpV6ZTY3gu5WZKP6Vw38RC0P+ZU1OOAprAJ2AJfjN07z6lgWfqjwiDrf3y+QA+POZEGfILkvPCyGltL2c69O9lR/QlQyy9yPEOa+HCdgTv0NaI5miA8CNeaeBxni2mF+W2qG79CMR41uHbSfaW6dvU6+W/w9ViQy985rVPqISjNGcfgJmr6nBrQ8PcqtakurfM44KPSRf6m28HzkCQ/Cx2pmK9G87YqwtqAKv8Kb/lnztp7/VeH2vueN9kbefoSqWWbHBPm9UIhhISUEMOuFrQzW36uIUmkFmKylrKZFh7uvAJBLlIsEYg20yCtDi3z84uUW+UA9xdPrV2MecdurJXForXbHDVGP/hjLOr7cBbvdBcLHwFvFXEzeGqIPDs8pwe2/h8i6VOvwBIGiSxZGcoCSsxiUmiG6wDXCPrp3/DSXNH4jo+dIOKqAdrj9HV32pml3Ib1xBiYwgp5hPyrO20iux6LM8ccZQT9svjsQ2xvaO+w7Z63AXtBzAXTI3jS10G3fjATIJQ457fIo8Thgz99If7O82EsI3d+DXPDJCyGx1u3v9XCvkFjr0rIpo1zr4pdLGQVbB79hStseeNSLJ2eU92qibboaWiX1U3b1iRuTQ6zH8dE4YYwqu/2Eb5ZydgGMKexuilPaZ5TAMePCZ3ekS9oFNqHXj7QLb1xxFC25R5VJR1qCbfGVFTyXSoGBJUnCTM5nykRPzxCLWdqeWMxyA4vZqrGYDglsvU/WXMuI0eX4R3HM/4Z/bLiO6x8FjWEL9d11/4eFAvpxfdgi6YQNFkt552gIrIDELH+IoA4P0UGl82HND+V92IzUrj0o/Ob/Iqx5z4EYr2bU0VEh3HakhXgHdtWFd836E2JxtDE7w1dhBUCsHLiU1kbM/eY8dHWYDmGuV9/He7Yfskr+u+xFYuCHGLaYC5n49MzhwBBYm12wNvIwq69y1gh1bGe8eOD/UX9EIl4bTTsxMIpWb2sTCpa4j3HxGt0DU6ZW4uKp9nqWY3ShgX2soyWBCcemc9Yx7UgI5C7ZbMtPpxssz9NFidVhnAfkWGdgMS6Da/w5EAEtrd8nLClCN974mWjlPoCsd5F+hA2bpDRJhUcteG2aUA5LblHeOtRCpxIUfp/YGLdfe8Ntk9RVwFmBpnG58GecEsiFKEj49p03CoQgJqp4tMeAoPE9/08IKvowwE+d2Ww878kIWnskGLiFfDsSySvwdVIrYraoLmwIgaTLDMFRzj5n4g9wOGoMnXPksJT3bZ1gGyuNz4J/QNxGWEcfbgXrtV3Jsqy+eh5vTzkCozsXxjbuvJRtfMX00bb4xfoozi8Yt0gr+H/iF0v+f+IXd1/TCsT28FW+8Zr/wyqr0y8wPt8GH5gF3/UUC3S9lTIaQK5ewIBP+QAuwcoIeIgSlpUyrjBJT0UzBPfnyhWqH/Oz2KtRbBCHNuAdc/qC9OWptOncs7YwtdLAO8Xcb9vg5w+GrU+FlWlmG37Wl+em0PqMvZ70M8P61ErCabe/W6Z9E+lnQmCspp/tE+d9YOL62UG2PIdwea6H5rg8TD/bDV3Ay6Cf2Xfy1Wliq3On6HmErc7yHoJJmyGtTrEaZqSa2+N/aaRSHz6B8hB8kq1Lk7YuNXltMWW5XBEOooMDefACzoMrxdd3tCPB7oFqxnpP7G0Jhqy0H3c1HKIA4jHO7R+X5PZPSpYixySGRgsPMoXDdCN8P6vOgeX2jMBfdARGAoUvvPY3xn2zOxoMhT3b4L8ROv8NxrRp/9vJjh6ecQ+8VuO/W9D+112z/ylhiJ/W/VLE1+DpktmpW1c46+1OyMEHGWLCRUoPgJOB4bYcDXFLTVgNY44ayyTN6Bim8Nh/hp0TmPanzp9rozh/PhrVtvHct5qSNyW8e5Vg0vYSqSlF7S9VU57wW/5+FQaeHUrbE6arFGSlQh/3XMUCd23D/H2uxQgtOVKEzxcL9mLUTxJ6X4X6SQnoJ5XZf/h7JMYyvaSjiHpJFC/1E1nc81U8Cu6OS8ch+nq1xytHtl1pDIIzDCYNOlh7JRsMBsHdgh2/3l4Lgiul0Xx4paYtVWIQ3Gvt2fffx657TGelvDWAw+pP7Ylew2Ygpj4BaYtcpZYdZ0LIA8BvgE/YkE/Y8CqehVqseWnjDhb9IP2rbkBp86y5mutDKdiLHmfWtLT5Wf6g6RXeHFHN0omfgtKstq/ffQz90GVkHYyEB+qneOQMUIhuIUf7WzlXivm9mgp3R5CVRi53oqs4AwWCRolnCXbKJ8nC5E45raz5k9vhpqGS7xsURQf8sb/x4rwzHH+YzWYsen+hM3UhOuiFYlgCt/2gmJuCaZPGHNHpupFfe0eBsEbUHS9GYfBU31MYMcZuhQJkvNUs/J00iWGx0kLaLnIZAs2PeL2Ai5iL+A2rBZJcLnof5flTmdQyQD1/ntaE8255X0jEPWJWhv7Zioc/F8d4+PUwG4f/UavL/7LJXiwGZjNu/MzpwFDBIWdYS4o3gDDp2zPLqV4d1/r6xr8iPxL9Qfd8HhlsiwNjmPx4geTHbYz4NEkD23H58TMAJfqVvtDkRjzdiajiKM/Qxcd+f7SQl0bLjcD8fxkmJkb2P8zOhJL/LfBBji5GcneVNP6sJkf2ho4wLglBMuAIFyHl3Wl1l0iM/9jdEqQACn4EgA7qaZ4i9bNDusC4X/Tcjomo5MeZwPjR4Us9SpnyfvUzqFd+rtLpll/TK3LNGFhTdynqib7uZxA4pzTjinJ8F2M03ioUZxNKu3IK0ukUhju0oiDNIAX4LW90RQpC5KPBpJMPB7w9q6vR7lKHlASNLreg0WWUkYw82DVERnSji9Pf645o6Boaj4TfN7LfYt6r8NWapzU9atPO1naWBn4WwVGl2VksJxMEU8085WPe9rtL2iZobWve5nFd03ZyO0viSYOdRWt/eKcW19V4gvYhEy06IKMnubqW3WnzQEIrsWLy/jCxon9CiPeVezRBug0BQ00+bNyMnMlQsFwB35KIfV/D8pU2Pssr6bRhh5DSEu4SfP3EQSSF5UQcInkymcxDGPJSyqXGq/eA1PgESo12xQ1Y0loMvL7hsmJgmHweLv8ti+DyX5vy+dibWsvnBvmvDfn8/bbk85u4ABiSz0kCLGxLAuTy+VedWy1V4b4wMeW1zv87MUUdg/nV25D/XpPkXWTJd8r7uDH/yPYWPSTAJT+aiA5gtWk/XTSo8SKXUJaJ6bI8mLqgzc2cd+tFzEF2Miy/j9+ytRNLKs+oVg7LQjI0SfRV74XtGykzuSgkVT6JXAqUVjIXv/7rwaAezqIbwT/bq8d9gp7QDTVluYIp6/tDOCVUqXcqJICRkZSh1CbYaeqt7A5FLZZF8/a75J1ILhYycoEcNrCA+LK8V2ewj+zgDHYipfLIiSQGW8AY7DeRIYro5BxR/QUYEmYl4ERfzghniC/uYIp7gYETzolm1F8d2oi4H7613yFvl+XFjq3w5Y0/w+1/HUP40lpLtlJYD8MZ1X2+jZ1NPHbfdjZX7xvW0CZWh59Dks2ja/wYgiNrNreVuoXDGlrPIVYteWkgNh13lBs4Su63kcZQHlf9IQzQkQLm+xA0rpSSTPkwxoyt3wM85YlKnaeMjuA85Z4InacYoS36RpwNBjEfDJuH8sE2xlBurSSGkhXPGcrnpjZEUgnNNZb0eIN4bGApKB73iW8tHk+KNIrHsfEG8Ri4RoOJcQ05i1Cj1yFezvsToKg+ZdbPtXu26nNUd6NuDHNsj3xTrsfzNb6CV3pL44lbY+xX4UELRtUKxS7/IBumrrEo10IH8OUkkOGyVZIOFHErzhlkWMWyFaEQVJorWih5XyLFiykdtmGoW6vzNBh1QtungXbUHYfCdlSfGqafbKtoHafJfQB3b9XiuS31HQSg6DBR5dMKzs0mnrvUa5C4VfMaSLr/R5mmvdHScukbRyq0N0DfMu5kjUhhEHtb2JF3oBnA3vu0bgf1sHc5cfjm95ZgzVoNd8jtnTCkA8eY7JY2RBBMjO63dOhwGSWmL96THMdQpidTYmYMM0oef8SFJI99/h4bWkzo2Bnh7/Ez/RLzMNdkzROh8wOPbLkM3Cu36HCfBZ3WvKek8qbft276uda05l2l/RYOZ/eZS+H8yhYNzjexENfQjpUC/cRLd61bPgAbV+mKm00uV9tVBTkCejczTKPQT+PhrVaeQE0h1jyCa6pw/29uW8Y6pfy5WZexXgPdU50G664M2MynNPdiG6LTV5s10enpi8wTSedgkeFoHx1eFbKT1/zWth/tlPKP0Lc74LerauHba37j3z5Veyk4b96sgXOrfi7Cr73waxsvtPymvfANPIWdnxSWQN4WwcKnKWIzguLz8Y/yEGwP9ZMdMJy+Wu/P1LYBio9/00AxsvZSUawIbWwUVqfTgj27iBlT9KGauJ2MDte25/uj21F+1C20O6Iwv6mltl1bAvrd8O7edgK7ToIxDqC4sE+ud/ptVxLNfNsUru1/i809xbRZdjv1axbOOv19519g58nkfNrufWfycp7nSMgWXNNO6f7r5VDpzV/5cuouLgleVe45HBKNSCw6WIXsjwedyvWaugt9F2y6nCpwm9633KJpvZohx2+piAHs6RIMG2fWpsuN89im1uOMIwEy4b0YvhCj9l2yEIP34UI8EaMvhIFG4UI8EPNfF+KjVgtxfcxlFyK6iS9EIVuIs418IVbvDZvgWxsvt69iLpngrL00wXwrHgupR7HgM9B6lBUHAc2vO87OU7S5IjdtvJwTfOnG/7Yid8KX1PbhK3Jgw+UGPGZj6wFjjANZSd7fr9+bk9AYzddnU9Ul65OP6dMs5dFtrc/D8O5/olGTnctjU4HRHNIjVLl57Fq0e81rtU6vRIekkT1OLmRqTNEh1/l7jGkgNiMHKK5gGCvlpcBwMuTf8LaRdoq6/jIcZ9wGzkYyZFWt28mn/MoZo/zvoPWCXj65XC9XbtD5VnkUzrJFtQcNn3/qci/uX2/4fLoG8QYgOco7+wEzYnag/qO5FkyUUzYhK4ovwvg9bXDzEXtI/otqaxmGwds3RbWxTa7l22TGLCPoI6NCW2Rv+BY5VMe3yBK2RSp4OW/L7jCMm1J+OYw7Ut4a4xbsZlSpOrQHFrJebiy/3B5YXB6+BxZy5KimPXCHBfbAjeF7YG/Z5UY0+pIRXRc04kFIH7xC8nfIRy5GCeTSCjBD15sFxZo8Fjof4niIDoiwpFgP3A+wk2YfnxSvnwqh9fe/FM+Pd9NpkN+gDn5g0M1rZnbmIbos5z08jkNnHTD45pBSjm+Wm+m4meMn1KHTNuCRy9mNeEJB9EqRzG1qdazFCndgpm0cCgjxrpTNmYE+Ijv9fgaTpMws5+rgBR5OZXXCP/Gi10yHO7tYJXmrVKiCVH+cVmYz9puaibelj8YQwyNmyd/FhmnIBmQKLRnyllbxcyWFM57NCIVcF2oh1+td9l9Fz15cMXuzGEiIYNaV9ULgZcF3YlayOjYiBPRw+2UU2S9PiN41FGJeGpjE7JfN6Ikcfx41P0nYKw3swOyXMFS/JS6SA9MtL6brhT2l8Zn286JvLC6k3MWWgeZoyp3kRkcypj3D/D5bSXpIKaT7DxdRSqSNrkA/6CZIACUoK0cRiDrs1KyWUL7LTHtJpjikGoY7Dy9XdY8vdct9bNwR6x54nZi7NMzf5zkBuu/93NyDR6fm7eVxmJscP3FrzwCyl02+NX6aUxrfyOw8R5kfFvTGmzPtf067A+AU7Qy4Y8jO47T/9sor0vhC1/jTGJpLEAoMuhXa2n+b9R9m4tkgYWjun1NB//id4i/FIQeQIOEYPRMpJKaPLVOuds2uxkBLFwBk3id030ohQMtJBhm3bLZJKVuVh0oQHl1sam6Lpg9Br5LcgJ3qdpxPMcbvYTzLRV9sjw99J7LeJTK4v4XZ7zMEAPk+RLYk1/j60sZZeHYKjXWNO5w2K/wba1MaStGUDp/GJYBVLm18FlvhwVCejU0uNiCX+Ho5HVMr1VRCvP9LKS7S9dc/L3L91cZuVlJeLcL5WFAXJnOCh87j4q5EvrjfxPSjKa09VX8HvmciVRypcWAynhkEVZgH1oFqZfmI9UiqVRLoTfcYI+lmmzTmVwCqVd9nTgNvOzFjur/vOPbLKc0uQXICyu+jmkJSrFwobDHczyHR/RwvFDHidsCfgKe6QLXazlut4YQwyzYGiOBI3q66Zqmury3jLfPCWvbSWqpPB0mwT5eAyIwxSPdO21hKBwoTVl4FfFBfpVDEuB+C/La5iRd509p0ccV3jH/ddxH5Vw42we50cElAXxBOY6GDp4JIsWfCSsv7XPJOt2yzyccw5rsOgOzbkGUDdtaNpD6MvQN4MoYWdwv2SgxtQ/Yf8na33wZkqwkDR6x01eQFf1z7Wor/lPF8jD+u8RSLBsUUGJgjcAydz3LBq3huyyH/KgG6A1ORCxiEukr+fjaCEjKnyEIOIbzqDK1MeEjRqk6hEILJQIrlFpd8nvLhydugl6G8lyvQvCHp3awpYN3sw9t9T6KTOgk7ivdbHm7BDVevXhn878M7tq6t4U0oaHN4Ucj0jLFJnmDkrPaMn7G41raYWhWiMWNqsUWMqfEcW3h+T2kopLpEXueQS5TDWCUXw+PuyoZadnaPNMFCJRJB4g58EQxeY6Jcza7Zh02maqA4pW5xuAJVSSb6PUTBaaeDECPjdg/wK3Rh1pnCCYRiPOb0VI4V0bnHvMncIzBlRKBfb3zFirdm5e6lTdzHhm1XozrqCoAUioT+pHINw3JxHksCmFB/Efs/Ja76PiOD+cvjeAtvF7obV6EDCLjVUzMDK0GCwsWulVKqfo7ncZ4DauKYPJ1SnHW/JJRiAn35JK5I5VrqasZhZcBaToqy9tMJ69RWtzXPtCVjhFQyAK0PXdZ8A0Cz5j8sX6t8dmQgqz/whyy85e9aQg68IBwhT+8rjQUEkHm76MD7ZFty2Hn4n3/hGvdqvG5rpq27RkeUe9dxEUn0ftTC7tBgEM4rpMCLDgRdyV4s5r7NGNWsifNDACEQII4OqOlqsK/jTdbDcZRGWJT90sKvFuvzixEW2cn/FQ7XwMxqfiI4sFwHs0sQNQ3kEZYCSVjq6ni2D9jwcF2UTtUtIFDXbAp3qJLD5YqoMMSHfQu4n3bifvkCIL9i0SU6cR1Glpd4LkSKXrzATTmJhwwCg5cuZZgtBRbqWI1n1wCrAVySOLyKsJp+D6lSGhgmZF1hSPyzcq3mFp0V5fglh89/ivIrLgoAAOdjhUXoC8wv7ugqTABU2vgMy/hbcmDGXSB4vVIgid+yU0Z0mwBuGjoji96LwU2NeIJmIvAdtZEM8lkP++MpQwymNR8NsmThyShH4BVBmfGLNpSs24HHWgnUGB+w7iTt4P1RlFyi5IBaX3BPjPM85kZMK1CW/IIm3FPKHT8jTHgK31PKPesIG33jBXYm12pip6km8TKmWxAMJ419bi3zKQ+znTdQYHxpEma3TWJ3qMyrE1jkTmJGWl2Z05ZMMYVWB6aQFsLue/ZbevL5ioZ7MG0o/Xryk1jKzOhIFGDOibnXR5pCN0ahWZts0ZTLnx/yAVERSKL9tCQO24WhLd6pEXTzJ3znp4aw7KHfW+iELEIwI21D2ga6vZEdHAKwLPiZy+Xb6LLD+Ai0DZe77Pum/oc+rMuXQotbaHD6Bw9XefJa9LHIKE/j0RQcqPj6FZgX4RDKmfN1EOuwhY87SJ/56VrEtuDqSH7L0b1rcJ3LJcot0QWxPOAGIPsttfX81lKEWnsdatkvahDDSj7P7MfRfsrID+z9SZpwMJlI0TNrGCnCbH11Ttsz3UQvo+HA7FoACntX4xDKKE/pj7DFlR4/6VLa5ybuSfnIxAOIg0oLQM3fw6kwmwACLWdwz3pM5Hw7KGqzS3CvGqgBnsfzv6wpYMooeFsuVYddJKGVwRdWpjKtjjAbcBjHg4Q23ZSVoLyRr5GmGCLT05kftLIubJn/yWrX1GH6iZaQXfb+fH0m17dwebMH/JCLPAdOeZpiRe93eFNMw9/FBUWehuvFBYXWjdmxnuoLnoZOos8XyREwEz1q9c0syzqhJV71UIgS1uuldD4uqO5pNuTfR4+owMyudJ/bph9bq8TVFOMeVBz5nN7Th9SvMQ52viFN7zGe+COHXxQ5Rp0dmh+i1yQT97AloQMrtwaJYznu9aM83i5eso+1TZr2iOQZ/AGeYMu61/ELZgiv6aTD3zE7OKt4gzDrdlDSM4RTyq8/M3dYP+jNKStbGxxCaf7iOYLJYS91iiMV6nHqBv39zACloaFFpfMcfP4kVQaW0+9w/reK87+i0H3BKEPf+mMLvz3ry2YDfjDRyHA/ePwN0Mn1MEp1JHxyPoolLBF2OWMzV63WwTCOmLPl/Y8YkcdUKHI5YNn0n2hXyE9FY4TCs3GJ3zGKh4orEXW6dyOSuUE14l4ExL2ISXIYqIgWPACr8xyd8apDxJpsSyfoYrIOidKF1zwwH/vPX/FX+5ePbW0Stq9GeNu3iyOP0afORevLJL6Od2fJpxywUteuxpWqV278iTnxUvGwjLIonx++mu7DzEYE/o7ojxv6Hw733RaUdiL1e613r9LypmCYDYIwD2v8mAKBYvOCaNPvUs1kgv4Pf8h0tmk/ccmMycfT48RV6XGDkrKvDOfv4qrhguQpFwYlZZ0bFJNVy2VU5dzKFrQqtBO9uwF2PPuQk66YShbU2Rc1vdbfY8dBRm1utiC1+eEMcYwNURw11DkYYOwdiwep00645TP3BPrdDIKHO+WYUr2Si5f7yPNXmmk/P/VPp7//zIMsoFK+Gi/0EkAuxx1oxSsVEkXPtxfYXbnjWLbOLEx4XK/YFO1Qm+8LurfGcvcZZtCJx1txx037BwFjdjRb/0SXvFeSNwFOJLMdF+OY3UwbrTeu3gllQj5btURl41GgirDR+D6zl/JdNm7qr368s85vqT5NcidTv2cXssQdblui+kfovIbo/VsTaNmP/oByfyEnfK9bOAlPwx/VpzwNsaIvDdqxXVQNW06lNNNAKxLFVW5bMuo2iXiTtBVnYcW8XfPawwveDaIvEv66mRyAScbhHdZoYit+n3b6Un6PJ+xC/P5dSrSN3yTrDO6VJCkwGjRflE7d8mkl4T+MNwJe9hW9MRSX2LdkP7eLingSSbjAJATOhWf51H/CR5RHvte4RjVMPWsPn7Z3jZkJLLTWYxCcOvt+GK9b6UWwNKZJfxi5eodGja5xekvBC0rCER0dynkW9HjEn0nTHgOqcBPGhGSNdtB1DKiQpJu05b/LKddnCOeVCavY+luVjYeR0tYipS3jlLYMKG1tqM+pRQb4Bjx64ha12MgPDHzHSG/v+Y7v+01GPznjQaeUX77TPHyUMzycmCYrm1eSuTQRBN85QElHvdeKkt60Uj/q+WskI6ablv1VYoeSZLzouZFR0qaThMXdocSZ1CPY3cy/3J0TiaeDU0+HfTvA8Bj/RDnMbTbsNUZCgXBhSKGyfyVbgmQnkIBE5cAPRjo6+geNjeRlo3GOw6wmQZMvzn7L4VoWwekpXbgeVF77TqenQUZPB3xnpKfXh9PTdgvJzKBcx4mVNyqcnsZejoJ+/61GQX9HCtrcwv1cp5T1K2BfYxhWm8y4Mz//qY3/i6YwPrzsW40Pv97EMUIIRy9CDT2/XM03Wn63Jn7vI7eB1CvjeFd71HeJdLAByMVh+LlMe/9GQYcjjmPoCj4OtE4WK+eoL5D372lA8HXXwLfpHUoFpBz6noOvd0MY+K5qZS+/HDQnfKNB8xjeG9IZegmp9Og/Z/euulElXkoFgMghft22EvUdShQznqdUa36BiO+8RiZ1+ubgubgcTkeQJn3Ggkn+AUNWJ2HirjAZeDfMVE2CaqD+6UgaJfXdOo1k98V3zBcwgknZD0NWB9EFoJZfasKEYoypUeMaL9nRqcrFFdqOhpkyej0b3lU/bsRNEVTmYqeeiwaM76BYv+ZL9FAYqp9SPv5Gp9K7sTwSyigwe8/CCIeUeQdpq9TrbYbkd37HV6nywl9D8t+Wa8uyGM+KbaAT7xoRJ2tdiIy/dQZaPHaW3VIQziiLz5AkOH+BRr8GMPr1zLe4y8uQfn0kMPrV/vP/Jf1aTcfKB99xjOgXkVHMDmEkYj9+9v8DEcML6kNE7DD39ndfwakWI2I9vmXFAUTEXv+Gp5rKez4YtqK3LeMr+qYptKKAUpuXGzYd+steXs5IVzqRrtRw0jXyLbaqk77lqxr/F0lX/Vfaqu5F0hUdZAQ5Hj6m5jcScpvxdwGXTZLVB5pDBATG//xXfPyvhsZ/EklO3HKd+NYzFvbzMjaDZJrBlS1hMwi8yajHZ9/wGTQ1/7UZ9NdnsB4Dxk434wzqlRHwMXWVUX+5rL9SbubG3ekhj+XNy1t7LEcpVy0n622siVl7R3uaI7O6o7UXhn8fDF95eBnPO4eXjEJD2NHfHjVdzrV5HFrrLk3oN1VLJ6v5Nidw32ZSyLc5pZVvcxT3bS7+ittQrojktzxx32ZSa9/mT5pvE5gg+TbdtnT0baJfU9L8mjlt+DOLyJ8JPzZQbt1Vmj8zA/2ZBxuv3SAEstGfmah6yZ8ZOr97QvTWt+W//E0/fN2R+y/P687KWRRX0Mh4NSVLo5wylzgqt7TtqExS7lzGHJUMEOrnIfnMZf/VLQ7Zj37KH5mf8hIfJfFTzwlB8k8z+iftgnZadDX3Tw6CeY6wu69qfQ6RnRONcdkbp93J4tBHd+L+ye3ivEotDn23lijm7kDsVdDevp2dQ3TKlXRMtHFqkct+DkEDIz6i+yi5oeX+wybd05uHChqgHIrBP9JetfQ7TCmHZx/ACwncfm8Fu+bXcvyQ/lpOIrfupeq+TtDRXtB9naMluYhnkil0A0YnKU98jg5IJ9o54C3VbfD/wkhhfXCg+rnSEUF2ZOsaTBpLE2mPzxEjBmlRIHO0fFvM/8n8nuQA3QGf4Q5Q4OXKxS8Y+UjiTk9fAfF40fsG93uGkFB8/fVwv+dH6Pfc9KluhyrU/J59uN/z9U/J72k6xCO0Xw3ze6oHWfROVmu/53h/wi8HTQa/5yTSTgx+z88OmsL8nvcb/Z7yQZPR7/n87+jtFOWZaBfuO4FKMyRpdsn01r5PlF+UC0vb8H9+GvJ/Quc1byjbeat83as5CeWDTzX/5+KQ/MdbesNa9tJa0uWWfsx1CYRoUpj/czL3f05SXgX8UMezVCw/HOBnG6+/eEkUVWdyf84+oNmzNaihYXsM3V7vT/jXAabBJ5F5JJgpH3HIp9L2oO+zknyfLOLNY/R9Jtx2wKQH8/yRKZ8jjdaJhO6sQw76Ezpto6Q/Mh4G9ieYWCnPyx2fk8hh6ZC3I8dKqmmnvPuJwVeZxOVp4I9Lua+SPJRqhubqdOCHMFeTfBZeftj48hjdIbntE/4yM/sQW+WezimgV6s3By8zmHZtD8bzSdhgrtfzuViE/RydO0WgW4f4ndxM3szZxxML2C15VpSp43PQSMrj3ywbqlHLX0HXPPp7/Eyln5OotIzdS/hJPN3nGszq6pSbpMAPWl49pWwpxRP7Ka0e6M/ZKxyeI0L2V5gc95UezLoT6J+Xh31Ntyo3LCWW6aV7dpEusIvM8bKrSD8J4QmfoLMKb7oKDJ4Bwqtihgo64DiUNOdmVKJx+DSNdHz7GI1kEI3kJO7LuNQ9oETEm0KNlJuW8ONPWGJEB48cZU1yBB5qQVkd69PQ0Q59uQPeLklQrgHIT0+U7E3TLJI8MzYRrwh02wuybpVklQi/fzRUDhwVP22np0zAVIzxdIvg+JN8UPihLvhK9m9458trdGtq4WGzFBhri1duXIL+osl9kvg63A/C9a3Q7ibWzlMcr0RjE/uf2Qeg+kYAkPLgv6FidgkuZhiFgFWM3IedfIE0Xv2SaDrCsFiGtwrgrRp2dWixDrdAXMxuDiaQgOL+TQ6992VahdfxBX+Yfel+dgeT53g8buFYZRGioWeAKSsBtuGPexnFjC7LfR/lHnRdlyt/wz49JfFy1SPF8/X3k/D97spYfF8uoi4S0R1Lt4ADvihD6ti1OFYQjuSdSmfWSxL20tZ4eH+xl+2v08Gw/ooX/6X+1iy5XH9F+8L6m/bX+pt82f6WVIX1d13b/WmBCa2WIWEJcyRBt6IXj9ahWOBpEETvJtTN5qHD2qNEuALPWDMDk8viJ4bshY/i5dDXOTwX+2bH57wk/CO7Xc5LEdgLuR37//wqtzcvZnv2Ldzh2HgQNM7K+jv9ToXfzzL+SeUkKD8t+j5Gzyt25nubJex/HVoo732EMyu1uu0nsnMwsKVeue1jHUU4Mmvxhvh69gdSIMH+Kg1n4KtsV5QCQRn8FHZ3DLqDrkRfGpDAmm8N74m+Z4moDu6E78IrytVaWwu29dD5w4t9RR8G+cCQn8gaxcqPsvJEIAxUzmTlSaJvKP3Cvu2s77I5vO+iD3nfuOtUG6fHNP6voN2e+bzd+1o79CapF1sM7d40tpuqtfsbtvudt8PbJ+fQhS73wXN1nZ63NNC/3RyC8WB8XAANtn6IeznBRNX9I6gaL9iAH8p/6Fn/Rh+9kkLPlMWs8hirvJZV+lll9/lUeRWrfJ5V3swqu7DKf7DK/7DX41ilG0fZLSSHc/z9BdH3fsDfVMRfs/LAxxQvQ9si2jPTZjbP6oFY1+NDQoxUWdERQ7tPYrpV82tO/4ipbS65NOcuWC0Mns6ZJWBeY4Z2O8tgym9+yKJ03P7FeI0WtXxfb8nS6g3+GltOopZf0HWj/peStM90/Ii2blpBhu/E9PZOe9/lu/B6ipGlGLwH1G/2LhKLbCyN3QTUSSbbEpEetpcWOv19cuG9GXelnaDIW23/aZ1P+ICNziWX4Mi8GJGoPZPwmVyqIjb/kkheEegdGTfgQ0pp1nLMnyUfo/vXTylPfaDF2VS8HxZb4guPLbE6MZ4KVVsyoRV/iLEll9DnNR9ejl69WR9O/z746/TKrDz+oYFe5TJ5e0bV5eXtzCqjvG0lL79B3r6tKlzefsQob3erCpO3ozaQhD3O37dhPZO8X6FQcaRD37x/OTqkeN67VO4OvqfL3ct3gqAgT5yvPMLbLdblaSssyvb3NMk7j9ttb32Pm1ByQ3n6WNsveds/0vaoT7SOVyN5DkU5fYWuXBTaOjEgC3b3NEfOSvqFWYr3KXve4+vCdpCmRxj2j2MtmVRu+SDM+OECzr3uPR0pPc3mLBBMhiYBs0jFcEWr0nMhd6Eg5Nspb76veVQWvsetOS+gM0FcuyMjbUMG0B65kFA0qNywhgIRkMq2xjf3B5fDt/sKWoz4FvneX+K3F9+/rHxRFNbfDwvbxt+HWlOsAdixTfnk/RDYY4Fi2SyzrtOBPpF1NiBEtgjsnG5pRqyC98JiCf8/9s49vKkibeAnpYXILYUFLQoYsWhRbuXaKzS0hRRTqG3RqmBakrSNTdOQS2kVaKAtNNZAdRFxV3dZb4uuuq5+agUXyx1cr3hZXXStouupqKAoVrl97zsz52Qy5OzjH99f30O1dM7vzJkz88575vrODEjZBEKfv5l+Gu25SYYX8JyQEbvA77skxE6ZzjXi2mY87eFgjmHHe5bQSUuYDIyTedMUoq57tlGzIyetpd7bCayDZBiZ03ymjHxzbUVE7/J15vR9viVm3ORmAHQadkhQ9pnYXhgWNADyowFi9gYMZf5mukQ1kUyfWkKdZWxOQi8vvJ/MfpK8P36WFQ/m0Brylv3xPRLb7gzr7lwM6+x9UEK1ke2FD5JRY0OLD/eV7EiiO7V0pJCy9BlcI73nSM+YIE4K60Ide7CF07GZ7nAQpCd9HuuCwmDo3p/dm4cR3xVjgonKCHQiNaeG174GTWZ5HbwWQs/Dz40mJdxBA3l/Tsq5DrQpA/WcehbtG6AC2KHMuugt7TUpcug+Zg1vDq1Wdzf5iLaWxjaxsX4yJIUyObWZqRl+JYOb03RmOkb3HDvnAOU6EyP1/Sb6/SRaQt/uD0Z2mMFAXtgceWUHe2XrKRzeeHkjWTbt2EleXxnCXM0gtZT83SblofaXyFJr6X4F7CcRJ6sEzcR4RkLbgzfOdXTQpKedUeb/LeGsGTgc03OC+kMj3dA/SSbuX93NjoeRL+bi94EiEmr+kT0Gitf9qzsVr6cgVqmHUBhDOPO/54GGdqEZHjyR8gr4O3IvqAZcG14ctOAQbmp/7GCo42V6oBspkSsNaceHpx4iA/jZO/NCW94ix8R0vE9ODs1p2/ouLlNte4+e3RrsopMtww7RmmJg6iHlxOh7lfc+swPeW8PeGyLq1bOJ2dXIJb8lgj79ChH0e+s4QbfBIz0S8Xhe+bNik1b5M2VbVPkzdeOvKs/Ga4bn/UdUeEd++6vC++he1n8bQkKBZuNXZNkOfi2QLw9yoRB9EJ9/4F6t+DwbF9U+KPl18bFohvfZl9Hl/68L7/RGzfbLmejy/55fFd6TmuEtnR2VXtuvC2+xZnhrmqL7v7HDW4Tn80CLQAn3824l7GGytBFrkj0k7FVQRQ3TrVoOan5wO6h5CwTXTg6Naj51ztAyCtcMkbo8PP322yWJ1vBN97AqHVpONzRnb3+DnKN82LD2ffox/fEN+jHp27M2y5+hTTM9ptPcZ9STcOu4ubk5SMcB0KTt+rvJEnM5RI7qvXUJbYeEpw+G98nD7iE21u/RUnZ67RukOT4ao/rh3eoRWf4sFAjGOP+dwtaT/ktxuyTnIXoGWMvF5AwwKBln04P7urfh/hJ3R84Asx1mESwIx4+G2G1lsSMtEVreBbPffp1Usdib7ElSOQR3erlSHM+8hxowF3Ml2Im76Ri5vn34xtdxlt0UIsVU+r8MGx6iR68VYXwGgL+ogwtbz/Lr8PAUz1LQAsjApNQucninbFaChpvt0695nQi9ffgEcBjyLMkjTfzZnScNLUlxOL7pD5tDx024rZqUFy4+Z94px5l/+iC0v/nLfnnhefr89AP5hjk78/Gg71x8ALRgKvzNHGxoyYO/W/vSc9YyF8QbWmbGkZk0w9ocQqCanoNe4M4CAgYaWjKJl3jDWvoQ1HAFhCQYWqyEDDO0WAjpZ2hNIyTJ0LIQhyi39SOtkPgdeHLnq1C+f2gKvW0a97OpU0/srFeWHcwLvYk338LzOj+EsnfnsT7kPE9yjifZN0u3/+gw3O9MPb9zv6GlUCee33kAz+/cnz5wh6EF7cHDZbr0dwzNX5ITzDKRfkFoHNK3I/RNQvsg3R6hLxEaj/TRCH2Y0ASkGyI0TGjf9Hd8KwnxN4XL+sFVHb1aFi7Tw1UFvbKFyy6CqxJ6tShc1h+u8unVvHDZALiaSa/Sw2UD4Wocvbo2XDYIri6jV6PCZYPhalDog8yBa/0Gqseg7LdBTR7azeq8l18EBVu+ntV59BS5gjP0mDTyPenga/zkVTxgEyo408md/fyXm5o/7c0Nxw/Bhd5/PUvOkSNnpKR29WwhZ1Dijfgz6Dq6mZRLR++mk2c9F+MhaNvIeWcDwLmduJbBV7adnESG3R0TMdAmB5qZtpGTyj4F53bimkfuk6PPXkNITjebQiBx4sEt28ntUWz8JdJuT6IjZUfXR9rtVSCA7S+AAOrDkSKmKMZp6f8+SLumV4inpfsN6rmeajnhxBCTw2qxA31W6BKU3EXK7yTsEuwWym/Wx2Bl+Oqv9czif5qcvZ7rJ7+GQ9/t9uRppubTOsP6Tl3UMIjp79i9l2vCJH3QkwBfcYZWDDNyApn88l04An6sixiw7T3blJecQ8bBy3HzkHD2U8/j+AdGtX1QzwFmccMEAuLwD8xMeAGw4a4WEsXsleg/7S5ah7UHjUrbj9pvbyPnlaNNEnQKoEYxkuKpAg852UHbXi2l1CTjnmF0Lsm854hzzBrSbidN9pzWw3R/d3oMJpk0CduTPXjmQPNXOrJukhzVbta9Ct76x0t05tPcvvEdPIqdrgJpj99NFyiN24U7DX6A8yxpe458OmYXMeTTEwl4jhqw/MD1OmjqSsZU/sU6rBffqazXWRGKXq9DqsfIwAou3EuDTlgWGVOpu0tdr8Nt6pPefvYcyWkccci6k4zkY46Hoo+wZ/Or7atU+/2OdmLt1zOBm39lCmnW7SRZ1VPNxgkhHjnm0C8g2v0oVhTjd2TOvnHMTh1JP5EItJ2nE11IJGJlghgatX7JXxIli/4hZXzJ0xa9jivpHN1NJlFLHtZ2dR0XyU96xP1bNANJ7rGlbnOI5Z6RKBUe80lMMXWvKnkbD73jje9j/mJ2HsBsPfIdZCbVZDRRXf85Hc/7+Fl47eYQ+STyMrfGE53bwgZbPHmhY3khAuVH2unwNu3HZT+Kz5XDc/uDuIs9FlPbJ7ORtxxRPndw8jkmf7VOkU/Rumj59KLFfdQYnAfH4DwgHz+JxOw7Vfk0d+J7dYEQRCZpGY7PUbEbWm/T8eupI3oFTfdPIEN6Hovazxsef9aD7T14nGut5IeIGZoZJZtCvljcj5T1iAI3w1ML6uCpBdFPGULEFiaP2MLsRAMlYnaByvUasylIwTxVelatuCoBVBA89qw5o5zfPBXj80NbVMjPt5F5pys9pBTIkd+Lvr2J3t7mJrfz5Beib1+y7qyqMBCZDT6cs4Z4kP1PqXr1PEDf304Pk+IXXA3CLaqa21gHtac9qj3GvWUIvpSYgKDxHTSsZWuIW0F06Wm0QXIlW5iiuHDNcPbiZyCxGD9L6BcoIIORUqgbv0LPniMfslIohWhvEa4WyGPrBl+hdvNEt8i6wfWtSjn0Q0u0bj1win57Kfy3Z+d068g61K0Oc6j3/M9tniq9nrtYf5d4It8n5xFNQMzNsk71fWtknYCFHqBr7Jl/WtC/m/6K7fu1KILOYGTIQb3/uQvuf742KkcfXRvRNAw6tCtEaip3FynyUePG4rTI+FOxxkejxusa8FPPkk+sjdT7A/LaXclZpuYzCU0jsG5+sYXUzQ1Rw3X8DMPFa0XDML0cR1mSUv1CrI+1EmRU0R75I4pSIk8myQdaqUkZ5lRoL0Sjr6H1lThqHp+IilMWSQ/UeANbDzdefHQiGzc+tYaNGy9Ce11ajeBY9G9bmOkgNMWB0tWouHqC9OpQg07KdczPUP8kLLcyC3T7jnazcB9eoyjUG8RGJo6chXQqkW6M0Umrzw/Ico7DzOK+PPUkacqRdab41S5cSzsq1fmpB8nx7qgUEIccZoptlh9sZiZrr7I1VEVEU7EQOzqYjLNctoaZO6hj4kVo2bdxDTN3iCQsUl//Ey2NdPtoKqEIrqKeGz+TX1+tpOoz8pk8dZYvgi2hY/DBluFafvKNvNKC9TVZuZX6TQ9uRYe9rij/Uev+N4D/Htw14xUsO+TEFjoyWp56iCU4BdpucjpkN5ETlhtfytcQjVicXE3MqTvp0CiZNIK4jETrDyO/nuPakbjnmU5iC2mPJrL8OhGkclpGU401cweT0ZGC0F7/TRZcfb9b9b+b+Z8YWYWcs5r5948AMeIC5dbDTd3R64csuvHJNLbpI5MNa8huCBhN+MdIyht5PgTck0pGe++YrHwwX6wh9cvAnhQQYsd/G/9opkPG+FmOa16RPFK3agw3Rk772/etYcOLrV2h/Y0j0azgTTluNTcgEimvaQEt72mmn3s4+19PQOrvXa0OUG4Oksry6PaY41mvrdEcf1obNR7THIw9HhPd34iX71gTKXcm4MymrimzPXv102y+h2o5TmeR0dGnmjBUaGhPor2GUUGu1yDM28hBSFRo/9EXkbcnjPk72fp+v/zhqrPnUr9pT5MlkIElnPBltSS99PZwcmzYt9U4z7DT3J4w9S9kIHOxD7/ltNQueVcQjT2w/CSzS2Y2/7c6Ev1BZhtkfTj/THNvXP1odbKjkcQZWkBYekbml+5Q4/lBkJaeptA+Muvaoc66rqU1wMzHcfy7CQuPThzhbz7Tx9Cyi06/op3tvGplROqbJhw9hmSONrPRqmlwT36/iX1i2EDaSb7Us1hq7FhNxWloIUaJYdfRXnP7IimYIQWugi981jl1XlqJ62urSJXe08j6j5Ywqep2khOe0SJpP0jxYBW+AZUivAqTtpI0w/Sp38ijnmJLuqL0kcVmshobYlgNihXObq4is/XfyFdCSD1PqfvJ0O7ydBILKaZ+pdH+7GXBSAbNAf0aqFvlgXBTq7D/8Vds1Dbk4pxpopoGc+gYpGG7HTy8sZLkjJ5YTMnlaP4MGbp1ZWT2KjL/uQJK0jT5ySBpiXVXYo7sA7X5PXASp6N7UF7njX83Rb7vLPp9Txe/b2i5Pg+p32bA9R4XxeNhFxDw0ib2yaLENu7GT96wkh+NZvYERFuZGczgpmgzgoFxTRE9fXsFm9wlesrZESjzcZNJZtZAWNOTKnFfAPjyj8m3r0Qh+hcAHURSDfULRSWAEhgqpagM0FkHRSaCAksg60G4z8HbewLqeCJroeGdD++AO7cwfcM6AuEehHMj+rkjTvX/ON66VrH3I1ZzdzuIsYUB7wyM2tcrWj7friSWBHQ4YTUuSkSFMaxfRbrrOTjkjzXWvNupGLFfkAm+TuakxBtaxiWQ5eInQXmmO6hIJ8ILUw+y+bFP4MZYuCEnURqn0hFI4yjto9JhSL++ndB4leqRvk9pgkrjkXZR2lelvajDT1DaT6XHkG6kVK/S/yBdRelFKv0UaTWl/VX6MdJiSgeo9EOkWZQOVOkbSK+idJBK9yBNpHSwSnch/aWRUINKO5F+TmmiSp8m3yelQ1T6J6SdlA5V6SakD1H6G5XeifQuSoepNIi0ntLhKg0gLaf0YpW6kM6n9BKV2pBOozRJpbciHU3pCJXejFRP6aUqXYD0+wZCL1NpLtKPKB2p0plI91E6SqUTkD5D6WiVJiP9HaWXq3Q00hZKjSoditRN6RUqNSAto3SMSvshnUPplSrVIR1PabJKT9twPpTSsSo9iVRCehiLhrkNnJ0J2piQ6YoK8LNiOSlfP0a3h7oPo9tO3cRPGXX/G90W6v4c3TnU/Rm6p1H3EXSncH5GUncPuhOp+xi646n7R3T31hP3D+j+mnN3U/dpdL/LuQ9w7pep+2d0P0Pdveh+hLpPonsz576rPvLeIMf91P0Tuqu58BdTd9xScBdRt4TuPOo+h37SqPsMusdzbiN1n0X3MC4cPRfO6QBx90P3ceq+CN2fU/cgdH9A3UPR/Rp1X4zuLnD3XHaWzZP/JAeX0x0C2urV4rR1+y/R7WFSXfbI6nw7lNdqDZ9Dp/HSG9RKzdDyL9JdykseZkLrzvWklxZekZyUR5ojt9bTvaDeoOdNj9wmSYnSjn7x1PQPmuzyQAgM7+zQEyifhji+hP0L9mkcawWPw/+wWJIMCw/A/ScDZLqe1DIWFNxReAXUGvo4Q0sH7ZxDC2147WLycGoXCUauD6jtCrn/I2dxMGYkuQ1e54BX6quI+kqkrY/PHqatj2sC5NvIYdW00v7o4yftD/zeICp/K1faH5f5lfbHLtruzFVqsdU+bMp14URdI9Zg/hoSWdL6+fstmHoSDdqQ2+NXjJlCX2ElJ5f4o6PdfosS7fujvJLKD9tvflwNqtbvJP8DLP/9SkQMrdiuJNsOPOynGSH/Dh/MUPZf0LA3GilPrY80bRKxwzzS1Hw2vulytXnzvS+GzVEH319Q5K2Os+yVsylKwh6Ike4Hu9fwQj9cw7pLYhv7RCwg/0okugdenGBoWUNG/O5IgRbPwCVYX0I6IvqWh5qkLorTQ0bdA6/iJiKmohRxL7PWz/0TTKgBhaFuslFQXuirgnEyazMv9tI+ap1fDx1US/oX3g+wT46TzjjYugQT3T4tmY6AfiN/DNc933Lt76wJgf6kr9EyVIdpoC29/3iVljjZPQOHs3ChnbFnsJIP8m+Xob5BVzA873Rz78jlF5vDgza4cBI5frVZd+BctzrupW89aGhFYxN5Ay0MMm+VJJYtqKGNy7g4ypkYQ4vazqfLit/HkuPyc2Q/FWEMz8Xv/4Wq0hs9PslLHF423h8l5de9ZKiJ7ohEpW1oXY8jZ/vOKuOxL/0ey1sv9hVJ76vnIk5+ZFMS6PTKJ5Yxc4n2jJ7fRNqlqr6qDX82z9bs42auVpPBpOzKp8n4u49etdErB1laMuHhByAxuZEV39lf2XH2o1CSezAkcGxL4u72QCkiv6ncmcPd+QWr5efhTvugAU+THQ5brJj1h0GZ8dSIb47OgHTPaY/vxBOori8O7cwL/YKf+HRsehY079fJL0Ja8zKzX3tKkspu9lnMq3eTOZb2hPefwri2JAXz8e9dSW355KTqpA7y966kzeRvwjr0pnu9QPcu2pxuJO9JPVh8dFNlx3nRPYrR7evDWbkboYj4xp+89/iNByGfGlx7dp64Zs/eUzclTHKSdTINt+/59MQ1r+89detODNKCI2zTT9gxbWRRh3zOw+TBy7E/Np0f9dKi6PU6Np7wgbCuzBLqxvDelps/05kvegtf1LX3VFlXz4pz7BwxufkLHdw3XyTjzQN7T5QdJDO3VI+j0wVyhjcnYtKu9dKk9RQQU1ZNfSlZRnddI/pyhvT9R818Ej4wV/JAMlKGVR1ZkIkT9/uaJXpCUqR0G+PG8YPsPk+q5yOZ9q9TDlVpPgP1FU7Sh/PPFISXJBaG/XuTaH2RuSMDZfdbN+0aYZ8Ht97aB6lo/7ORFBrm5t16KOp6qZnmzs/j5edr8UtfqWMvvy7UkpVC9Di7+S/qg/IG8IXe8fZketsOt03tJF7NXTpTiLgs6Sf8A7JxGbVhbc05nDfHRdFXuGPkFZ1O746s34CoweOG1qnkuaP7hP0WIvI2r/56MxtRHS9/URcxDUKj4fFoNHwlm5X8Un6slsxKov+ot1dG1SdSHamSCsjsHBQu6EgiMwVoLXwF2hMZg7MlQ+sleNDYmQT/YEQpBN2EByO9guUcHTt9lxN/gNI4Sd7hjhyWNqsv3fsc16WQ035CSyQyekaMCMz7JQzMRBcn5pACjwxaV4ZWxuPCsbZ1OrXXvWI4YP/w+IL9eQn0MXDoSc+0PStZNtdQ8x4baTUsoR1jTBqwhXCVaGlvSLSk9/rnFLQ36fF0l8h+XiRxX8JrCtubEgvS9/tHMz+BLxgJvBq9X8+K5ET5/dvoG68nb7zOAm8shEsIP/Ky6eQ7W30KbXP9KSxUQ8spHXtpHHtpYXpDYqBbCT+/9WSgPxS2vsfRtuGWglcOT3vhn2v+fVmusm9Ne4LucWrFhZva/Z5uajfV0j59zuPkAJ/Akm12smD6hBmP+j4p/66WjHTsM4S2oI7X3EbGlf0vYL9m1m10D8QZ8LfnaRz6ZUe4ph7C41dw575GsvvLiZ57lPrHn1xEslP+E3m41/yTPbnM7LQkF+EGDuadXw01h+OH4F6mzf/AXQLH7StoPmszrHOQXQu+71kaNd5htv2DqaeFzmpbXqcmx827dabmfTpLaGCyPM+FRcVAuqHythFkCyRcChjS4Xq+SlPo+viC9n6gFIP0qFsk40J5g6TCzIZEaMJh9fmIsh5HfR+8wBLOY2+jr4pPlj+qoXs3v4RvgZDN8eSlphCUmP3wbWrgOKOSRN5JCkbI+QK0YcLN7WimG1r/hnsdvBo1v0tyHKPVMhQnQZhWtH6FPr+FfwqwVdB6uCmpZzvdHxFKHajj9AXp+wwt5JSBk/P6jvDL5HyY8OIECdrPraTJZjJs3Nfc2wfacCb9vry2acmGll52Tl94cfJkU/vsbTq2k+Ilt7GNvnBxpuGFvOTJWf0NLXPRptB20hS+QdeWN60IWo2zqPGHKfT+0S5h3PV/biNfemtX0w2GlrfIFmAJLz/GTOS64Bo6IeHpNy8iVdpY+CMvxZfi0mD5QBXVui7425N9KrJwxnob2USo536y0FdVtLRqeLJT+RCIvhXY9karnO5taOSZQwlZEIeeHHge+zw6czghVEp3rsA/hrzjEJv7StFYSD7kxAbSAGWQNTz84etp36xIrqomnSiMAfhvAP892edIEj98lCaRpG5uKTNc8g+Vh1XRaT5iprYvPhkkuW9fXnwR+aCvTj0UzEqWAgMw8yDrPyP2hdPfK4TnPyY7bCRvkOgiQD12Ov6O9XKGpERna5W66ySxbNsXmeYm91MgJQXhVTp+tnOYkzxD4vm3EpILfyzB8Zpq3D3rO+iA0A5kePjSBaRj6auiHcd/g8+16PPZatKhwm2tiXgyFigdKjPn1YFe11XjFjxn6ff9xhmW+aX0tSnow4FZiPLEO9lXISrGh46eUXOfpmVxNYl3Ty5p5x+TH3CAr2E/c+vRsI+VQvtYb1ZHBqvr6WB1XYzBan21Oh1lCu1ruB5iEOjA8eMqlMVP5nYyxYQfxq3VkTFsfzJJI47hHpbHOpX5KDq6jYu5gup4AI51X1lJav8UtAoig9VKff81NEWyE+5Wdju+hYSUvadDAfMpsKkgnYL5KkihYJwaxiUUdG1QQF8K1qmP/EgSkr1ABZ9TUKuCdyhIVsEuCv6iBvo3Cg6pYAsFqeojGyioVn2souAnFdSyeKhgMQXT1TCuo2Ck6iODgj4qGCfGI4mCK1TQjwK9Ck5WEfCJCr6g4CoVvEtB63oF7KZgherjWQruUMGfKJijgg4KQmoYTRQcUIGbgj+rYAkF61VgoSBBBZkUjFfBNRQcVcEICl5VgZ6CVBX8VCnE4z8U/FMF71Xien3QV/1uSTphGP0L0VN6eeHnws+Fnws/F34u/Fz4ufBz4efCz4WfCz8Xfi78/L/7QZOfmyS6LTVOQgQ3Bs2liUlDfqf/wdi25aK61dI9N0tSizQ4uFo/RL+pAP0CkG6B3yUsjFvh1wq/FfC7FH5t8Gtn9xw4igu/VfCL++E74bcGfl3svht+67j4LGN/vfDrg98A/C6H3wbGb2d/V7C/uBfOjY3v1j/44hubgr8vvuSOK58YeCJt4vUT7pT/ULp76LeffjdqxnV3vDH7x/vuzze8/Fnusqfe/cPbC3+YdeP+hj3n3mq59+p5B9atla5N3L1927hLRr/94JTLli/88bK9xfff+J8bG0wbvCsXzXii6rnHP3lz9XeZK/IMf9lZc7lxtP0lw6JZj/35Sv+mr/8w5elPVjaun7Rr+VMvlIx6YsP3j2xsufGYcczAhtZ3xnz2u5p7765p/G/y3xknSUNj8D5xOFF+/s9gXWz/D/WJzTs0eJZGOIuk2HytRjyf1eAYd2MMfkgjXddrhLNXI54NGunyavAiDf6kxnsf1Hjvsxrh7JJip6tJQ563aoTzo8Z7CzT8b+gT+72vaYSzViM+6Rr58qWGfMZqxOc+jfdO0uBHNPh7GvE8osFXaMTzLxr+v9XwX6nhf4dGPO/VkINZg2/UkLNfIz69GvHRaXxfWFYOicFPa8R/k0Z8pmvEX9aIT7dG/LdpcJvGey/ViOcQDf/bNOIT1njvdo10PaYRzkqN7+sjDf/TNOJ/m9b3ohFOjob/qzXCr9UI5wGNcAZr8ICG/vyo9X1p8FEa4ffV4OM19PkOjfTerMHPaMTnCY33zoXfMTF4vEb432vow8Ua4Y/V0Nv3NML/o0Y+PhIXO1/m9kU+QtqCBTj8TGbcEM94TjTHfSeQl2dG8/uVcNKi+Z0sHOPsaH49490CP8TCNwrhN7Hwu4Xwf1bCyY7mVzNeLsTfzcIxCulNU+Ip+P9BSdfMaP5ZH+bfFM33KuEL8RzMeHlGNL+HpbdbSO/Tin8hnIeU9M6K5otZOFuyovl8JXyBP6b4F957uRJ/IZ5HlXAEnqHklyD/00r4gv+rFf0R/O8n+h8vlf+BWrA9RG9L7yr5KKR3iSIfIR/rFf+CXk1R9Efwf5blY7eQ70sV/RfC+Y+iJ0J8tiv+BV6rpFeQf1CRm8CHKXIT5POxEn9BDyWrtaq2zm31+Su8fqtVshaUFlrtDq+jyunzO7ylhbmuOrejtGKpy0Hvxb5jtTVUWCud7gqX83a8dHi97jqrq85W4XfWuSWf32ur9Ui+Rp+tzl2J9931Ti+94XK4ATh9dbYpUyEaXn+dyyV5vI4K+4xpUsDncjg8kgeZ1ep3+axVDr+1wm73SuDDBS+QljrddmuF11vRaHW4HLUOt1+qddTaqr1SncfhhjAwKPENks9Z5aj1+Bt9Dj+6IUTm8njrbLUVvhp4p8/ZYPV5Kpa7PdLyCqff47RLHqfHIVXa3H4XBMz5gLS7HNYKG6bWZ3W6nX7tu/Aue8Az5b96sLnqfA5tH3YHJKOuEeMLIpd8HpfT5pB8bo/X6fajfG3+Ro/DuhRzQPLZqh12KySvorISY9ZIsgPkg2LyNEqVKMD6Cq+TZCUnToH5QIARVltR47C6HctFv9GCDkC+YY7BhdNdBb5cAQdRA8g7qbYGFKnWg9nsdjndNVJtwF1b4YGrpVFR8vlBIb1S5XKv049XXjcqUy3NfvF90tKA0+V3ulEF6yCNECC8AJKK+WujzzjqQUsq7RgU9VUJ6u8HbxAzp7uyDm/A/5LL53DUALbVeRppBngr3FUQBYfbjpc0YCLLSiZ6yDhbDSqp31kLmkLeV+FnPmvr6h3SMl+dF7Qj4PdRGSrxrfBW1UsNlV6HQ7K7UHXhj6+xFv6lcbS7qFL4qgN+e91yt1Tp9wbcLHBIXMCjBlVZ562Be1aUuUQED1JAAQVsfgm0S/FI7zkaHDblJgeITkVxlF4UcPqocmIuRd8ANYsCTGGjGCiB2+3wRjF3oLYCnq4C70KAdoiVl94/74FYIdlcFc7aKLIcpHKeJ0eFGwSHn7dwK0YkSG4uj0IVkNn8dZ3XLr4CdScq2eSbjUJEz2KmN+r1Dj98yd5YUfJUN/qiOChbpd1qg6LPH50zPofwblKYRREs46KfOV8V6h1en5NUG2JWwIcUHRWXUxAjFuZRwAvfI1Q+dQE/fBXnifc8XXL4bF5Ms+DXHqj1QFC+QK2YYn8sXLEUPkOFuJxLbRN9dRNnSC77BCiKAg0TGtJmTJgxDeEUaZ6lYE6udcrEqRFXxDlTdU1JU52p0yPOaZGnJkbcUyLPpU6OOCM0EsJU7ikep0lo9K2T+kC7p4/6nw7+i5MSiLuvyvpI/VQXfUZPri9iPvqzv/HMD/13APw7EPzT60HsjnJ3MPdWGgMD+TdR9Rev+sVwlNj9X/+X2C8y3vcbp3OQBKkZ208Zpxgs9e0X6QM9d/emvng1ibFLiH+DlMGu28j9wVIeu76XXA+SFrJrGv5AEj5ebyT3B0g3s2v/COdFEkjVwa7Xkft6aRm77iDX/aQV7Po+ct1XWseuh5PwE6R72PX/kPvx0gPsOnApht9H+jO77iT346TnWHqD42n7Tq/045mjTeBFI9n4rMATGd8scOW6a0o0l3+m7e0DAh9ynPJuge9mXBa4/he28mRqNP+A+dcL/FvGjQLv9x3lKQKfzMLPEfgI5t8s8PGMlwt8NuPVAl/EeFDgtYy3CbycxWeLwOuZ/60Cb2W8S+D3Mn5A4I8eY/IX+BPMvyzwDkX+06L5DuZfL/BO5t8o8FcV+Qv8fcZzBP6tIn+Bn1LkL/Ah3zP5C3wk40GBX8t4m8DTGN8i8CLGtwp8PpNnl8DLmf8DAs9W5C/wWuZfFvhk5l+aHs1vZ/71ApcV+Qt8DfOfIvC7Gc8R+EOMmwX+HOPlAj+gyF/giaeY/AX+T0X+Av9Ukb/AexX5CzyNhd8l8H4nmPwFfuRbJn+BD2f+ZYG/yfxLM6J5MvOvF/hUxo0CL2A8ReCLGM8ReCXjZoGXsfSWC7yJ+a8WeIcif4FvYv7bBN7J/G8R+LPM/1aBv854l8C/UuQvcKcif4H/pMhf4L/5gcl/ZjQ/zuKpF/hY5t8o8FmMpwg86TSTv8BzGDcLvJrxcoFvZrxa4AcYDwr8ZhafNoH3Mv9bZsauN7cKPNFJeafAlfq4SyOcboHrlPpX4MZ7Ke8VuFJ/S2mx62ujwI+zcixF4F3VlKcJXKnvc9Ji1+/lAu9m4VcL3FhFeYPIWfjBtNjtgS0CP8TC3yqG08zkL3ClPdGVFrv90C3wV1j4ssCfeZDJX+BK+0NKj93eMAr8eUX+Au/YxOQvcKW9kpMeu31SLnAv0+dqMfw2Jn+BK+2bYHrs9syW9Njtlq0CP34Pk7/AlfZQl0Y43QLfrMhfTK+dyV/gSvtJyojdXjIK/C5F/gLP6WDyF7jS3srJiN2+Khf4GkX/xfDXM/kLXGmfBTNit8e2CHy5In+Be9Yx+YvvZeF3ZcRuv3ULvFaRvygHFn6vwJX2n5QZu71nFPgtivwFXr6WyV/gSnsxJzN2+7A8M3Y7sFrgiUx/GgSutC+DGuFsyYzdbtwqxrOJyV/gSnu0SyOc7szY7UxZDMfG5C9wpf0qZcUOxyjwsYr8Bd7VwuQvcKW9m5MVu31bLvARivzFcFj4DQJX2sfBrNjt4S0CNyjyF7iHyadT4Ep7uisrdvu5W+DxivwF/gyrX3oFrrS/pezY7W2jwE+xdleKwCc3MPkLXGmv52THbp+XC/wYC79a4EYmnwaBK+37YHbs9vyW7Njt9q0C717K5C9wpT/QpRFOd3bsdr4s8I7lTP7iexX5z4odjlHguxX5C9zjZfIXuNLfyJkVu39RLvBORf4CN7LwG0TOwg/Oit0f2SLwxxT5C/ytZUz+Alf6M12zYvdfugW+UZG/wIMs/F6BK/0faXbs/o5R4M2K/AU+mYWfJnClv5QzO3b/qFzg9Yr8Bd7tYfIXuNK/Cs6O3Z/aMjt2v2mrGA4Lv1PgSn+sSyOcboFbFfkLvIiF3yumS5F/Tuz+mlHghYr8BS6x8NNEzvobOTmx+3flAs9V5C/wt2qY/AWu9A+DObH7g1sEPkWRv8CDLPxOgSv9ya6c2P3HboGnKPIX+GQWfq/Alf6nZIrd3zQK/HJF/gIvv43JX+BKfzXHFLt/6plIuWhDFGQcNxe9leNtHLdyvIPjNo5v5nh/jm/huIvjWzley/FnOF7B8U6O+zjexfEVHD/A8XKOv8Vx3l78A447eXtEjq/i7Rc5vpTjxzl+M29/yfEAnwGTIryKw3qO13M8keM3cTyJ47dw3MjxBo6ncLyG45M5vpzjaRyfyNsXcpw3UDdzfBLHizjexPEyjt/O8XKOL+F4Ncfv4LiH45Ucb+B4Na//HF/J6z/Hb+P1n+MeXv85vpjXf457ef3neJDXf44v4/Wf4xZe/znu5vWf4w5e/zl+Pa//HLfz+s/xMl5vJ1PeT6I2xKrecjyO11uO9+H1luPxvN5yPIHXW4735aPD8X683nJcz+stxy/i9ZbjA3i95fhAXm85PojXW44P5vWW4wZebznOl9ENHOftNoMc5+082zj+G15vOT6M11uOD+f1luMX83rL8Ut4veV4Eq+3HB/B6y3HL+X1luOX8XrL8ZG83nJ8FK+3HB/Nl9scv5wvtzlu5Mttjl/B639qhPN2v3qOX8nrP8eTef3n+Fhe/zl+Fa//HL+a13+Op/D6z/FxvP5z/Bpe/zl+La//HB/P6z/HJ/D6z/HJvP5zPJXXf45P4fWf41N5/ef4NF7/OT6d13+Oz+D1n+Mzef3neBqv/xxP5/Wf4xm8/nM8k9d/jmfx+s/xbF7/OT6L13+Oz+b1n+M5vP5z3MTrP8fn8PrP8Vxe/6dEeB6v/xzP5/Wf43N5/ee4mdd/jhfw+s/x+bz+c/w6Xv85XsjrP8cX8PrP8YW8/nO8iNd/jvP1aTnHi3n953gJr/8cL+X1n+OLeP3n+A28/nP8Ro5TozmftLTR7/BJcxcWX1e8aIEV/ubmW+eaLJY5ptzrpEl2R/0kX3Wten9RSb7VvGhefqlljjTJX+uRJvkafZMqfZNsVd66gGdSraO2zts4sbaiQeOOLeD1oiVv/g1z86zFBQvmWfNMpSbuEn7zS0o1aP7CuWpU8vLnLJon+b0Bh8TMIm8haIkxn9gt2vtLEyag6dqE2gpPtvrYgkWF1gUL8/JLiAVphnGsD7wxYWRHnJM5NwTQgJcup9vhUx2TVZdyn4hSdUxWXZHna51+dKAJaV2AOKu8Doe9ERyOhgqbn4YHV+yuz293ujEZdarT7oBgsgmz49vG2pXko52dRKRVVFCUb801FZlyC0pvksa6AhTPuak0v8RaaCqToiRdcENBycJiaRIaSGM2EUPZQketqb7C6UJJZsBLMiCU/lJxfpHlJvo0ytBakMcuQKjXFVgsJaqYi/NLi2+yWgoKC0pZnBbCWxbk50HhTyNjKs01QwBlUsBNjCsddmmsb+LYAPxPHZLd28iFV7KoEHRvYXHBzQsXZI91YXSEm/NN8+bl52WnSGPwdgb+M8Yo1U+dOGViKggMLZNTp2ekpmdMmSEVVjQap6Qap0wGtwXtAiVqFzihfqqUOtmRWmFzSDdQW8gMIyhJf2kOmtaCG68IWFhCroz0tslrq85Qr3Lraj1Ol8ObQa7muiqqfBnKvXlOv9Fc4aum95TMC/gcVpu/gQrnRhCs022T7A4bL60Sy8LSEgoKTfMhz6izYAE44UtZWJyXX0wyXyIW1SmV9vHGq+orXOONaeMk3nZ4ok0qyc+/zlqSX0od+QvyQE9cdvJPJFJOtydArO5Vm1NjJSiFw06+G8Vg2bo84vRyzuUSNWwOuGvcAIy2Ovjk3PRZxXg5Yph8nolyxDb5fKPkiDVylBlylP3xeYbH51scn29qzNkY88bFsayKeXNi3mhXtXDlLIcjJsO8rTBnJBwVtyiz4PPsgc83BI5YAHOmvxGbX97YN8rKVzTvjZjxxrDfjTbcFS12zzPVFW10OeNcstiCV6TzCy1r7qJitvqB9wjljMlYmm/JL8TixZiSa1604LqScf2lklwT1gimUrN0IxQK8BnQi9KCwvyFi0qlooUWizX/hvwFoO9FphsXUGAqnpequqZIpcWmIitWewXz4IvKl0ocfiPkgK3GU+d0+40oIoeUB0k8n4qpN95CSv4lUp4D13r4jf46IxWWVNLothmpSI11lZW4eiFKssasSvssqZiI3uip+N/2rj+2jeu+k0eKUkT5qqSOojRu8pLZnpyZMlO7ruDIiShSlOT4hyrJtjJFsSiJkphIokpSjpKprVI7atDZjtImhtdlmLZmqVdkm7oUhjZshdekngvEiTEEnjEEmAMEmYdtqbFmhtckfPt+332/x7sTTzSQ/jX4APLDu+/7vt/v+7737t6HmVwqMSasTWBrFSN0BzSZiMeyYMqyOTGWTgzhIMkW3tMWvfsinX2eDtzLIFQt5tSemhyY2K7R9BMCNw4MCbgAqrmEp8uoevU7agz8Qk9SzdcY6eyc6Yw9IHr3Q8RxaCIY3xMwCK19UDTGIUTj4DjksQu6p1C9ttBdlZwTsMhsFqcRsg5FhJ6fAmMgaJCpQsRpiKiTdho8XTCcBMTUpcaY4D0hlnFnJPu7yUw6hENSWMewutAIfQby3b4bG0INYG6ByODjYiABqZqNRmVE+wtKnp3pEWs2KROUQtQwIIIMyH5lW+z1Ztgb0QvmfwbMfx/ogC2ypqmMEzVo59SEmJpIDaeSQ0azshlDgbowOArmV7BhMS/n0jDMKauUOWtcY8mRxOCTwmYU6UT1ONFLm5eGsIsr2yvUppR26MEptVlMnYsnUrlRLOBwaqRgs0VvfGektatvuV2HyKEnUdt0J6ZFVHSMTY2kJkQLTAxTas9ZPAH9GabLTAjUoJPCLIJKhc5uLKOi+wnuK3TjLP7OJcc3ocukvtYNbRqcnFJhi4UDGX7CmwYT0L02qcrbvCmLO+AKy7TF3Fv2cpWnB0U9YHjXJcNPZRMjSXt4moK3Caz1NBoi3KEkyO9T9QpdUuD0iPVsnQXFcCpDtVCqHqY2DUElJCYGzZKZ6RrbsMj6iqGpjJmMsv9mOBpfQo1WaB/WqIvHhKoHAQLcqfbgBlv8LnqOfAh26uNGrGBHJ6E3UH8W64wrYBsElgfOK+36rE5DLY1dHDrMJEQ1yRaFNDeKoeRwYgr3T41grDw8wipKh6/Z1R2D4W641OSN0jLQl9HdVI5l+L4vbRZ1nZBUWyInDEHoK7ToEtqzeVtoeCyX3p6YyqXhp/LxMym4CYDhk8hCJuhiEpymXGowBKY7mVGzCTqlSjaeyI2G1JZMOM/BrURoLJ2eDKXG7acHoQ8plY726LZQbLeqk22h/dDC8J2czmUSgGMbQ09tzCTHMmlb/bd0du7p7NsmjL1rltm40uMSLvvk+LJgzvZYl922TomdISu3f9bDSPA3FI1nt+ocU6IOJyD4sQFyOjYlElmcSqBpZ9Qp3jsls1nzvB38gjSYM+NM/Yaqy6THYZYzIg591oPy153OQR+NZtLZbKgrPfg4+CzdGdwQOmhkVNn/rKhbV3/f8Lp1G8xHcZ+9foyoujOpkREYWSNj6QGcbceTmZHkBMwdhqvndANF42g6k3oqPQFTyGMJ0Byqr6/H5zgOf1I04qiEeTU1NI0exEQOvh9PjY1labHLdFVFI09FEALnKNy4Cj9xIlU/LeHJ7xW9odxMKD0TGp8JjcyEhmdCCfNRksVXVg4A+wJ74nH43tkCV3rVbU2fJbxy4ckRUAF797e17I629NE0zeEMV8II1xHvmVF+DoQ2b4H7rN4+hAGfGH2L9p0AvXA/3Lf8jkU0Uiyqxg6kVDUUakRNFw94lt/7LNcrlMdy0wQtMKFCwWxjiVD0mjmm5/foEovUsMC5WKSyYiA1kcg8KdIZMZrIiuxocgAmME/hps7wIxphYMC3WtXAjKfha3gCstKFReBI4K5RUJuAYU7lID61HGL2m8Jdoy1adDxFbyIzkqVe5vHsHQNrFxpGHyLJLgX44XAC1hVdNZVkKpm19gcMWTS/yxPgG1tbcLWVGlsQ1fpsz9v5WRk/G/M5ZBpd89NzrwA/K9JXVQUrb6ooD5T5fZp32bmwpfIw0r6o+HyWOPlTRbiKUCf8HOHNhLcQfp7wDsIawtsJawnvJLyLUBDeTXgPIT7P4KXGTTRR4Ooi/67v6enxOt5T4HLO0vHhd6Wc/V7xz3n4nP6eu/x6Pk79X0F6796al+W35eWJ6sJnbY2BKMPfe24zflvDOD9PW+RfIf1TcO0Htxrnp1z08TqHc8aFiJ95h9z6+WbNchnr99UU9Ptq3PM+5pDtqLHj9ZabP39q0cvfanxWiuOXLvKba4wP5r/xtpX1f2GJg3//ktKeXyH9eZL/R81yfcQNkG4Ntr9LXfwCrv8YPgdvgTB64TMC543wCcHn1yT7EWAZfPw0jtAWtO7ei/tkT/stz1I1Oudn3t47fPfv1IxnKaPevByF30uBvGyCwXztC5B/OG+4Iy+XAEfX5CX++9PZL+ZlD2DFXXm5AHjtt/LyDcC6dXm5GiI/CzgGeLEuLz8BrLs3L8OQodGNeYn8JT2b8vJ8GT5Ly0s0WD2b83IacHpLXi4CXvtyXr4TwL0koFeO77zn5SOAS/vz8lXEcSgzYEMmLzdWQDp/BfECtl0BfcCGm6S8jHi/lOImiB9wC2Bds5SHEVukfAewokfKRnBTrj0q5RHAnoSUHwGeAFwd9HguA24BbBiQshvwWcAc4EXAFwBPJKW8iPIRKdeAkXwWsBHw4ijYAMCTKSnfALwG+D5g22NS+sGITk9I2QF4FnASsDYt5TxgD+Ai4EnA84DXAK8Atk1KWQ1G9wRgWMc/vAV9wIqDUk4DngRcALz2ddDDcE9DfsA4131LyibAacB+wIZDUE7Ai4elPIvXn4HyAl4GXF0N8X1byjbApSNSziAeg/wAjj4v5SeAJ8Cu9YOxr3hRylcB616S8hrgRUBBLxXwuwLepzo93ulq7x1V5RW4BWItPYe/lv9U9QWPXh3Xa3d8LvhExaznwS/cf+/mteqx+Fp6Pthfm5fqeWxEr57TonrtIV+rLkb0WjiP6BXqnRZ8P2wawm1E4z+iVx/VWvTaI76YLub8Eb3uUFlMb9L6KvW6iC4iem2zXt2sV7QFtcP2K5HXz7x5DuP7O3w+d3te7sf4QPac1qzXHvM9pItD/lY9/PVKWzQj1tNYMAancT7dEcQyVEE8ozCGtlF8xzQIP+fbgfFpJypVWVRUDxm/W/SK1uBe8/euII3lbtDvhzH4Pg7cAV18Q6/o0YV2shJ16f0efM17o4DxYs97sy6O+lv0uiNlET08F4joDYfKW/Xzs34tWak3wDWoJwjTzBlvCdLzxLMQT9XdefmCh/MOYY76WnRxxB/T6+agbsOHAq1QwY9U6uGYqlEzlkgQpG32a7hHBssDdqQb4q3Gif1RzGeLmc9mzGcM8xnDfMb0fu2oXoGt89bbHXr/ofK5wJGyo/5jvue03XpDfFnmo0WDav8AJY0uCxwJqvcMFiE/74D9imG97cC+1rIqoL0HvbbjTEdVAM7bK+GkNfgoQiSIdf0+6FxZCzYSHaVOLEOrvQyqrqNYhm79kubLeIvWdSu33Raoi0vr8/KKPb6WIvHt0k/7fN8sHl88SO9aHIb4ZjfkpXoUr8ZP16pAx3O+Y/6jZUcCh8p9b3qxMKrv4DrQTyD8/O/AXIN18JC976j0282+s0O/5Pd93i39Vrje/joIzoDkTRCdA9lbIHxbr9gT1Jq4MekdDPyz1oswJ9R4OZ9xHOfQ7rsreaC3BLXX4KRFnUCN4XgYAr3Tobz8PdI7BN2hX3u4Uq+Oqh6M7509C2HWwDyDPHhG/23H/tuO/TeC/TeC/TemL3p9z0BxsCzW3toe1Lrhatx+FdLHd2VwHF4J5+VWs34jRr6F7x5Nr20zLJTRttVg6/wwv+36Io/Lne7j8vRa38/Ki9ZthNu2H+PryMtP8eWrr2LabasC7Za2favM6KiU/jyEfycJ86u/ZF/doS8+7fdNFm/ch4LGewyXMP3H8vL723m8QPpxI/24ysC/1BoZ2AXfRnPHYRzBiNSOBI6WHfM/5/NtrzLziGXaAnN9xw/zcqLJUiaK86sqzl/VsgL2myEIP/9vMF5quf53rAp0W+rgxZsweCzo+44Pf8RJ76UA+jlSfogvEu2kdGKo14qKe0Az99tGQr4xzfiB79ahL1L9JSnZh8J6vQzX1sC11/GGa5dbvdKYWbjbt8fvZoWM+BrAn3mpQcr/XtGmUHzz3/L7/lBz7Si4SPosxLcT/J5/voXHdGuRfqfavV1fqPK96isaHdRhk1awwQtVVsuK+b4C6byxS8r/XLEeuH/d7fuD4vWg5h3MN/KWDHVL2WXWw4rzmM93zutSsUOc7TiGs+Yb/ZCTkM4j+6R80MM2BEzD15QFUX7KWZDPgLzFIg8/UZCjf/nqCvIK8C/fXUFeB/Kq/cXlOAzaQN4I8r/RbPNvs91+tcP8ew7sVNRup8CyYxxHII6lh6X8Y69LHHHDBvYPL48CJyfM53mIY3Wvez6vgDwG8qi3VD7/zDWfW8Dn7ngEfFeP03ex2+qO8eVRtFA+pyGOdx9xr+8TIK/qKy7He58lkDeCPORf7j8V+nHc8EsmHy/a5+KUFz+gSLjnZS3a0hXkMZDPgvx+q3y8IB8C+cIK+odBfn4F+cs42Abc5W+APLyC/H2Q97vI0X/3w73OPMjXlJn++6pAyzHfEf+hMu2v0a62BDHcRrpnOu5xzP9hbU6vjappFOeHblyAgnuqaLklPuucV6mMdXuQ3gk8DOEF3Du94LuOtlz0PuZmmdHXOA9x5TJS/r61rFqb4WvApIj18RGEuZQpXh/oL6yGe7jqrJSnl5dzZyUXFDoyvjfaBGFfhrDftfvxEcs9zeTX4JYmarn5wDGA6cyAbsWUlC850+nQEmY6bUaeT0LYGQibspWrV2Ua/eKzIH8T5DX2e5cI3rtAxmEAiCjfwKCtQJ1PQGcJ7kV/VFZUx3fcZ9WKBVEH72e3zEj5sT2duKHTr31qVYG8Y/sO4QLkN6T8c+16xmq6aPM2B419PosQ19CslPUrxhUx5skO7S/1nojefwC/OzRwd3uien8sqH3bdVLD/K6Ge+ww3IMnvNeThk+4zWgYF97Hd8N9/O3lJeOC+dE7WTSqaFCN01dxjeA7Uv7QY6l77C9N2vdVd4Gg2FfegXCLEE5x68b0at8fabq53xP7P8gnP/pU9uPCbzfmKeaWJ9/PA8sLZkzTykcoTNKeG8eN48Zx47hx3DhuHDeOz3ZIOsz9POTAMB+qk/+UnycHyu3P4avpnPd0vkmOCu/l9P+JEZLXipiXlfcm8l5N3sPIPKy8R5H9qv/JS2O7+aIRH+9pnf17r7m/Vu0P+rFxzi/u/JTyx3tRax3vDVym/bnsXy2W25/b8HNB3qt55T2v7XrHP3pt+VyggtzkSC8vjfw3nfFy/aet6V6h8wd+bsj/l84/vNFV/18dCxuLe/IB6pA1hOsJtxLGCfcRDhMeJJwjPE74CuEpwjOEFwg/ILxKGKDN4zWE6wm3EsYJ9xEOEx4knCM8TvgK4SnCM4QXCD8gvEoYoAFdQ7iecCthnHAf4TDhQcI5wuOErxCeIjxDeIHwA8KrhAEyIDWE6wm3EsYJ9xEOEx4knCM8TvgK4SnCM4QXCD8gvBqw29UawvWEWwnjhPsIhwkPEs4RHid8hfAU4RnCC4QfEF4lDJABq6lYeb5wzhvmvljiv2a+TefBfNcmv7XjYH7rD130mc867KLP/NXMN+k8mK96r4uc+an7XeJnPupnXPSZf5r5Fp0H803Pu8TP/NJLLnLmk77gkj7zR3/sIme+aOYLdB7MD93gImc+6B0u5WP+5+0ucuZ7DrvImd/5skv5mc/5eZf8MX/zay5y5mtmvjjnwfzM77noMx9zg4s+8y8z35rzYL7lt13kzK/MfGfOg/mU97rImT+5xyV/zJc87yJnfuQlFznzIZ9zSZ/5j1Mu5WO+Y5Pf2HEwv/E6FznzGTNflfNg/uJRFznzFZ91kTM/8TUXOds15h/mUMw77Gb3+GC+YeYX5tDm/wL8emV95hNm/mAzNPGyflgifeYLZn5gDs28wOES6TMfMPP/cmjm/XWzu3ww3y/z+3Jo5vXdW0Kf+XyZv5dDM29vf4n8M18v8/NyaOblfaZE+mzXmX/XbH/Sd7P7Zv8jOfPrmu1P+vMl8s98usyfa4YmXtKlEvrMl8v8uGb7k/6FEuVnPlzmvzXbn/Q/LqHPfLcehz7z2rrNS3wwny3z15rtT/oNJfR53qp21D/z0u4o0X48rzH/rNn+pL+9hD7Pe8wva7Y/6YdL6DOfLPPHmqGJl/NyifZnvliPQ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' [native]=$'0 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' ) + + +_forkrun_bootstrap_setup --force + From ab46a27b15a8cc564080fcafc5aab75645b48335 Mon Sep 17 00:00:00 2001 From: jkool702 Date: Thu, 21 May 2026 16:22:48 -0400 Subject: [PATCH 02/10] initial test - superscalar prefetch engine --- forkrun_ring.c | 257 +++++++++++++++++++++++++------------------------ 1 file changed, 132 insertions(+), 125 deletions(-) diff --git a/forkrun_ring.c b/forkrun_ring.c index b51843f9..87ee8e5d 100644 --- a/forkrun_ring.c +++ b/forkrun_ring.c @@ -605,131 +605,9 @@ static int ring_is_spawnable_main(int argc, char **argv) { // --------------------------------------------------------- // ring_exec: Ultra-fast path for external binaries // --------------------------------------------------------- -// Superscalar prefetch pipeline: -// ring_claim → commits prefetched_batch to TLS globals (or blocks for N) -// ring_exec → (a) tokenizes N (or skips if pre-tokenized), -// (b) spawns child N, -// (c) non-blocking claims N+1 while child runs, -// (d) pre-tokenizes N+1 (overwriting tls_argv safely), -// (e) waits for child N, -// (f) shadow-orphan-rescues N+1 if child N failed. -static int ring_exec_main(int argc, char **argv) { - // Usage: ring_exec [fixed_args...] - if (argc < 5) return EXECUTION_FAILURE; - - int fd = atoi(argv[1]); - size_t length = (size_t)atoll(argv[2]); - char delim = argv[3][0]; - - int fixed_argc = argc - 4; - - // 1. Ensure baseline capacity for fixed arguments - if (tls_argv_cap < (size_t)(fixed_argc + 1024)) { - tls_argv_cap = fixed_argc + 1024; - char **new_argv = realloc(tls_argv, tls_argv_cap * sizeof(char *)); - if (!new_argv) return EXECUTION_FAILURE; - tls_argv = new_argv; - } - - // 2. Load fixed command and args directly from Bash's parsed argv - for (int i = 0; i < fixed_argc; i++) { - tls_argv[i] = argv[4 + i]; - } - - // 3. TOKENIZE BATCH N - // If the previous cycle's overlap already tokenized this batch, skip parsing - // entirely — the kernel copied argv into the child at spawn, so tls_argv and - // tls_map_buf still hold N+1's data from last cycle, which IS batch N now. - if (!prefetch_tokens_ready) { - size_t batch_argc = 0; - int ret = do_tokenize(fd, length, tls_batch_offset, delim, NULL, fixed_argc, &batch_argc); - if (ret != EXECUTION_SUCCESS) return ret; - tls_argv[fixed_argc + batch_argc] = NULL; - } else { - // Perfect cache hit — bypass tokenization entirely. - prefetch_tokens_ready = false; - } - - // 4. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) - sigset_t set, oset; - sigemptyset(&set); - sigaddset(&set, SIGCHLD); - sigprocmask(SIG_BLOCK, &set, &oset); - - // 5. SPAWN CHILD N (returns immediately; child runs concurrently with prefetch below) - pid_t pid; - int ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); - - // 6. THE LATENCY HIDING OVERLAP - // Child N is now running. Use its execution time to prefetch and pre-tokenize - // Batch N+1. This is non-blocking: if the ring has no data yet (scanner is still - // ingesting), do_lockfree_claim returns 1 and we degrade gracefully to zero overhead. - if (ret == 0 && state && !atomic_load_relaxed(&state[0].emergency_abort)) { - if (do_lockfree_claim(&prefetched_batch, false) == 0) { - have_prefetch = true; - // Pre-tokenize N+1 directly into tls_argv. Safe because posix_spawnp - // already copied argv into the child's address space — the parent's - // tls_argv is free to be overwritten. - size_t next_argc = 0; - if (do_tokenize(fd, prefetched_batch.length, (off_t)prefetched_batch.offset, - delim, NULL, fixed_argc, &next_argc) == EXECUTION_SUCCESS) { - tls_argv[fixed_argc + next_argc] = NULL; - prefetch_tokens_ready = true; - } - // If tokenize failed, have_prefetch stays true but prefetch_tokens_ready - // stays false. ring_exec will re-tokenize next cycle (safe fallback). - } - // ret 1 = no data yet, ret 2 = EOF: have_prefetch stays false. - // ring_claim_main will do a synchronous blocking claim next iteration. - } - - // 7. WAIT FOR CHILD N - int status = 0; - if (ret == 0) { - while (waitpid(pid, &status, 0) == -1) { - if (errno != EINTR) { ret = -1; break; } - } - } - - // 8. Restore signal mask - sigprocmask(SIG_SETMASK, &oset, NULL); - - // 9. THE SHADOW ORPHAN RESCUE - // Child N failed. We already atomically claimed N+1 from the ring — if we just - // return failure, that batch is gone forever. Escrow it so the Bash retry trap - // can safely reprocess N while N+1 waits in the pipe for the next worker. - bool child_failed = (ret != 0) || - (WIFEXITED(status) && WEXITSTATUS(status) != 0) || - WIFSIGNALED(status); - - if (child_failed && have_prefetch) { - int node = (my_numa_node >= 0) ? my_numa_node : 0; - if (fd_escrow_w && fd_escrow_w[node] >= 0) { - struct EscrowPacket ep = { - .idx = prefetched_batch.idx, - .cnt = prefetched_batch.cnt, - .num_kills = prefetched_batch.num_kills - }; - ssize_t ew; - do { - ew = write(fd_escrow_w[node], &ep, sizeof(ep)); - } while (ew < 0 && errno == EINTR); - if (ew == sizeof(ep)) { - uint64_t one = 1; - sys_write(evfd_data_arr[node], &one, 8); - tl_drain_escrow = true; - } - } - have_prefetch = false; - prefetch_tokens_ready = false; - } - - // 10. RETURN - if (ret != 0) return EXECUTION_FAILURE; - if (WIFEXITED(status)) return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); - if (WIFSIGNALED(status)) return 128 + WTERMSIG(status); - return EXECUTION_FAILURE; -} +// Note: ring_exec_main has been moved after do_lockfree_claim to resolve +// definition ordering (it references WorkerBatchState, EscrowPacket, +// prefetched_batch, have_prefetch, state, tl_drain_escrow, etc.). // --------------------------------------------------------- // ring_exec_splice: Spawn binary and splice data to its stdin @@ -4351,6 +4229,135 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { return 0; } +// --------------------------------------------------------- +// ring_exec: Ultra-fast path for external binaries +// --------------------------------------------------------- +// Superscalar prefetch pipeline: +// ring_claim → commits prefetched_batch to TLS globals (or blocks for N) +// ring_exec → (a) tokenizes N (or skips if pre-tokenized), +// (b) spawns child N, +// (c) non-blocking claims N+1 while child runs, +// (d) pre-tokenizes N+1 (overwriting tls_argv safely), +// (e) waits for child N, +// (f) shadow-orphan-rescues N+1 if child N failed. +static int ring_exec_main(int argc, char **argv) { + // Usage: ring_exec [fixed_args...] + if (argc < 5) return EXECUTION_FAILURE; + + int fd = atoi(argv[1]); + size_t length = (size_t)atoll(argv[2]); + char delim = argv[3][0]; + + int fixed_argc = argc - 4; + + // 1. Ensure baseline capacity for fixed arguments + if (tls_argv_cap < (size_t)(fixed_argc + 1024)) { + tls_argv_cap = fixed_argc + 1024; + char **new_argv = realloc(tls_argv, tls_argv_cap * sizeof(char *)); + if (!new_argv) return EXECUTION_FAILURE; + tls_argv = new_argv; + } + + // 2. Load fixed command and args directly from Bash's parsed argv + for (int i = 0; i < fixed_argc; i++) { + tls_argv[i] = argv[4 + i]; + } + + // 3. TOKENIZE BATCH N + // If the previous cycle's overlap already tokenized this batch, skip parsing + // entirely — the kernel copied argv into the child at spawn, so tls_argv and + // tls_map_buf still hold N+1's data from last cycle, which IS batch N now. + if (!prefetch_tokens_ready) { + size_t batch_argc = 0; + int tok = do_tokenize(fd, length, tls_batch_offset, delim, NULL, fixed_argc, &batch_argc); + if (tok != EXECUTION_SUCCESS) return tok; + tls_argv[fixed_argc + batch_argc] = NULL; + } else { + // Perfect cache hit — bypass tokenization entirely. + prefetch_tokens_ready = false; + } + + // 4. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) + sigset_t set, oset; + sigemptyset(&set); + sigaddset(&set, SIGCHLD); + sigprocmask(SIG_BLOCK, &set, &oset); + + // 5. SPAWN CHILD N (returns immediately; child runs concurrently with prefetch below) + pid_t pid; + int ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); + + // 6. THE LATENCY HIDING OVERLAP + // Child N is now running. Use its execution time to prefetch and pre-tokenize + // Batch N+1. This is non-blocking: if the ring has no data yet (scanner is still + // ingesting), do_lockfree_claim returns 1 and we degrade gracefully to zero overhead. + if (ret == 0 && state && !atomic_load_relaxed(&state[0].emergency_abort)) { + if (do_lockfree_claim(&prefetched_batch, false) == 0) { + have_prefetch = true; + // Pre-tokenize N+1 directly into tls_argv. Safe because posix_spawnp + // already copied argv into the child's address space — the parent's + // tls_argv is free to be overwritten. + size_t next_argc = 0; + if (do_tokenize(fd, prefetched_batch.length, (off_t)prefetched_batch.offset, + delim, NULL, fixed_argc, &next_argc) == EXECUTION_SUCCESS) { + tls_argv[fixed_argc + next_argc] = NULL; + prefetch_tokens_ready = true; + } + // If tokenize failed, have_prefetch stays true but prefetch_tokens_ready + // stays false. ring_exec will re-tokenize next cycle (safe fallback). + } + // ret 1 = no data yet, ret 2 = EOF: have_prefetch stays false. + // ring_claim_main will do a synchronous blocking claim next iteration. + } + + // 7. WAIT FOR CHILD N + int status = 0; + if (ret == 0) { + while (waitpid(pid, &status, 0) == -1) { + if (errno != EINTR) { ret = -1; break; } + } + } + + // 8. Restore signal mask + sigprocmask(SIG_SETMASK, &oset, NULL); + + // 9. THE SHADOW ORPHAN RESCUE + // Child N failed. We already atomically claimed N+1 from the ring — if we just + // return failure, that batch is gone forever. Escrow it so the Bash retry trap + // can safely reprocess N while N+1 waits in the pipe for the next worker. + bool child_failed = (ret != 0) || + (WIFEXITED(status) && WEXITSTATUS(status) != 0) || + WIFSIGNALED(status); + + if (child_failed && have_prefetch) { + int node = (my_numa_node >= 0) ? my_numa_node : 0; + if (fd_escrow_w && fd_escrow_w[node] >= 0) { + struct EscrowPacket ep = { + .idx = prefetched_batch.idx, + .cnt = prefetched_batch.cnt, + .num_kills = prefetched_batch.num_kills + }; + ssize_t ew; + do { + ew = write(fd_escrow_w[node], &ep, sizeof(ep)); + } while (ew < 0 && errno == EINTR); + if (ew == sizeof(ep)) { + uint64_t one = 1; + sys_write(evfd_data_arr[node], &one, 8); + tl_drain_escrow = true; + } + } + have_prefetch = false; + prefetch_tokens_ready = false; + } + + // 10. RETURN + if (ret != 0) return EXECUTION_FAILURE; + if (WIFEXITED(status)) return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); + if (WIFSIGNALED(status)) return 128 + WTERMSIG(status); + return EXECUTION_FAILURE; +} + // ring_claim: Superscalar-aware batch claim with prefetch consumption. // If a prefetched batch is available from the previous ring_exec overlap, // consumes it directly. Otherwise, calls do_lockfree_claim synchronously. From 41983a2cfcd4b78fb11c1ef397d257c8b38068b1 Mon Sep 17 00:00:00 2001 From: jkool702 <107448833+jkool702@users.noreply.github.com> Date: Thu, 21 May 2026 20:28:32 +0000 Subject: [PATCH 03/10] build: update embedded ring loadables --- frun.bash | 2 +- frun.new.bash | 1746 ----------------- .../forkrun-libs/forkrun_ring.aarch64.so | Bin 137464 -> 137416 bytes .../forkrun-libs/forkrun_ring.ppc64le.so | Bin 202656 -> 202656 bytes .../forkrun-libs/forkrun_ring.riscv64.so | Bin 104032 -> 104032 bytes .../forkrun-libs/forkrun_ring.s390x.so | Bin 140840 -> 140840 bytes .../forkrun-libs/forkrun_ring.x86-64-v2.so | Bin 142120 -> 142152 bytes .../forkrun-libs/forkrun_ring.x86-64-v3.so | Bin 146216 -> 150344 bytes .../forkrun-libs/forkrun_ring.x86-64-v4.so | Bin 150312 -> 150344 bytes 9 files changed, 1 insertion(+), 1747 deletions(-) mode change 100644 => 100755 frun.bash delete mode 100755 frun.new.bash diff --git a/frun.bash b/frun.bash old mode 100644 new mode 100755 index b589a16b..cca6637f --- a/frun.bash +++ b/frun.bash @@ -1739,6 +1739,6 @@ unset "b64" # <@@@@@< _BASE64_START_ >@@@@@> # -declare -A b64=([aarch64]=$'0 137464\nmd5sum:54de4aeff7ba78fc838ad65445d53893\nsha256sum:adc4fe608fcb0e644ab378e86119b4221616fbd8a2edc4b08398842db4e7f377\034\035\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' [ppc64le]=$'0 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' 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' 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' 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eetPk80t/SgmeaykUSwkezrBSNZdF4fXyTHf5g7m5ruIfozz+P8fAt5xI9ONEoLrPR7WHo0FVoIj6QcLYJkduMviO19xxA3zEMkk639iKSjEehdEhQg/lbaUv2FTNgjEhDfF6lZWOWigSivZd+4E79xnBa1DzySQvYmwg+xvTik9aT1aLmJ87dnsQexp27i22E3Jatv4vihmJKVN/Hd8S/qfdVNnNxa8e0NZagWQ570hg/xCR7LrN/AE2mfvwSM4tXu8jbGivPGnDONxZ5IahlIfmEjDc1HAE/LOou+W87pY4phYxoPbWmJNKax8EhKbIWS7psYi6LNgmTAedrbECfOO3nW9BX4KYaVAQb6C0tWFlDb+1uwYgxUJJYddz9S57k3IjuDdP5nItpzxLlFRM1O3oj0GqTeFRYk+eU3Iv/iX2whQRn1EyegQaTj/okwUu0sAmDj7/A6435x3nhKbabVtSA72LgVn/33nNWHeB0bYhY0qw04i13LvJHT+GWUnHgj44K0dyn5ACTJymAzmohlTQzBJhCplFlvu5EzUk9RnetvZKyI9hAOtjoKsMOV+d7qC978BNnaAauthmoTbxGv8ZHyUrzGIgWGRN8QAT/WCPxxNGQkSIr17S7MfBQdrBavwf1mKeK/UH6nHcsPqMKf5BZJrpUKTg6VChoiJaFUqmzJiIcGnuEN2ILVE8VrXKH6qC/NGvIp4pzM3g9K3iGjoCSM6nBGDDTdLS7CokYfCwbVCbBKpdZXoJzwONQNq6+9AC95+kG5+QFJPotmr5pYKKcqh2HoA6My41fZaLr2yqfU9kdgCv35Mw+gLezRx4smhqZAUhKew4GgAHSVgDIbCVe14vJX3xuOK2gVSKXbS0lwYDlUzkplLrtt6DARJPmMNBhsL3iBqtuklBMg0kryY/Y4HHuS0qOXf/eL9zm9xYLT8duMOCjafD204S2JgveZ1ZICJVGgTlL6VsdHWPwnXhyl9K1iT9NQ3E6EDvcqQjud+v0hNq5ubFyBDLtN3qf2PcxGVq0k/AOarnlTVXi5laZyp1SrUa7vdGp/5tKaTtTuo7z8wrDyWw/x8qFeFNE64lSgcjrRKdcBEPQsB0RKA5YvqLXwEdRU5VJDA95Zj+/2qTspO4+UqImQf7qM5RewfJxuyGdzkcE/NlFfn3XrSC8+y56kOo9Sn2Z73HJZmq8uY0IeEpZQRbejzC2OKEOFRJIxb6HX68ZgtyBfaziC4MPbR8WMeoQByJxPneuwzZqlxvdTgup6eOmWSyXU3b9CIGOdK8IyKtDpQZI/mPGnlCqjvOQtsknyGLtNrTqIahB4wlKBMRECFM2szkPy5ZFPux3b5nQ191hrAvQycaGUXOmWN3lwU1VHeZLhpyGqZnsIXvMQO9eUmr53PJEMCPJ5mNoFpTi1Pey4Gk8eYqvxJVuN6HI26/dQdl5wDsz6y5A/vpTl337IWI3M8am+E6L/dRo+LnacWnI4NAcam4OcTqY5EH3vYukTC9XdB3DYL9toIgJTrDRsLTTsk3Om4HLEkYYINUqwJImm9cZVUh86zFVIegFJyGfwR/Cg3sHAebZzFbIaoZKOCkkcWUgt6vgqWQubT/ZtmFTt5SDON19/Bu5zlhNIkSGa16fyNOnaKMhdKK6McMqn5VLvyZmZUeLK6YIS2zMJNlRdZkJKfmpWUBAX5RdUXxldLlutkF+UdZcl81HK9zUioc0Kglxahtq5rEaQdq2A/LL3By21wbVIpVbhh7LXI98h18qbCqrjshFWg2m+9aJrU3Qh/RbWfBiCB29Dv4x7oFPehr6iH3mJrJeEfqL/X/QUgepj9lX8vsC/7ysT+Pf9Y1D/uV/MI/v3SBggVLdkfkMV/PdBGotlePC7PimS+lprac4jqSAR52MV0jVSirEGe/AGyaBc12LMI3v7tkBNiNgEsm1bEeZpXb0NvUH2pwH1FX0rGdJNTKlLzZ1l7yDJ21chXZM99hhXrsfeUd1aHQy6xJUue4dVCLHwCLmwggqUkMS0CmcWMMY+5H3hCUa82xgxMgrYwSzGKn9yNVBQWKyxVyNiDsENm8apNCM4jU/BE5vGJn0ZfdXGuG7lo07VzeyrOnPlMjlZmOgNlIeZrcOB7q/Vtjbr40cgEIN5ofXXfkK1j5xwoWcEr3SGVcojhkwiEE21kKSah7uA9eR7QW+LNzO9GQvq828JzT+y6A8a38cV9l+N+knkVLRbkP/E/LVRrP1US837+D1sJ/MFvQ3U1XVuNrMUMG8poh89FWjefOXwpKWE4KDferlC23sRZghNxnmkl1HhNUFYtBCCMJS6VkK5fuvzcnVnCCq0wBIqhNLW6xcZlGb2NOYwi88hTN+hHsD1dG+hqayAZ2gi4y9sx9Fe57OEmlZq5Ap9aFkEHm9h9T1sJbJ59Tv0r9u4T0SehS+gpVmLRBUjPmLzuXrzM4I8F2rBaGo+1RPXcTM765FcyMsHL4TKAyRp/7qgr5PzYedDzgfd8lbnmAcfkLKPJ8JEAXWMIQamHiq75fqU3cCGeORjeci3Am2JuScQc5Mn+QAS9zjJUQg4skIt2qdj9Jm9M//kvTBeXLAcUXh+uuOw+FZ+/Q4puxgbf/Rx52POx51POP/C+JDee0AWRYVbhtXb0DFz6jrcmOoPsB/THcenyzVrWT8luQiwP/IFuyT55DqEUjVrD2MqOkrJRRk3SkJJzX6gF7vD2ruGtfcUtFeDfF+6cC5ld80nBn0g6wIhaI43igTtxSBq6g+RfxCfG6d88UFJPg+s4RbEIyZ+j/rjko+qZ3az3sRib1KxNweRf7zH6M9v2J+hq/CDtMukwCy7zQV8ng34vxiEXPWWvdDNr4nPANzhkVU2W0Wm7yHxKiPPKf4OPmLmP/11bN0kGBn65wTnSI5aMQeFEOfDwJZ7O0TAmm7GVYclN7jdXsG43DH27lLgIcEDaDHOE1iGTlyewNJpiA9ll72HBH9sEyQlD19MkBwL8Y2Y8w8i3/AqLaUO3va/gchc4JN+4+j3635Y3K3EABOxa1Sg/53yKU/yGY9wWn39dzZhfUTfXCwilLode0Xvq1T8FUvNRpwHwnmm8asXdhJ/mbEFWS96a4KoiQvT/esz2rvLyM0tJb9ooSewEqHWI9epHyK4yGXIShdNcMtplgnpcn87rXKofejC9E9N8wkj6nGDRR+iR/kkEYeTLhxxlrazpDvOzZiaDhzbc+LaKfbuAFhJpciWHAAxIWW9Rw56AuMEYFwE1boL4fncjCSPfEY+6ZGPwvZRK3bRBGRudGYNtgNN2E7rO8seZ8mw4ecA2Il7Tck3DRE+shvlLHkfcKI9pMD8gWMJlr4eOJp26z5P4OkIKJTB900g6g6p4EiUBDMqyYIEa2tT32GgKvryCJGlweAgW1ybYe8O/YPeUTHsYl/sIr7EWXugFKfhQeRJhXvlCcdqcXhub4kAIxO9w8hMl+JxnJzxA0Bhpn8tkmTCqTXZOBs4KzAnauMOKIj7LI74ARy6zwqPMNWD2VQHrP9sjyJQczBOEn6XlKiBHtmu1myAcXuBZC7AiXoQfWIOS95D1YC1kqKwZ7NtKXVqRxgb+cXkfsjlj6RV2AcA3nj1WQAeQGDxCMqJatJO7DGKCP662c9L3hagxvOR5gD7fL3ok6n+COhrwzXPv4ByaWCMPank9Kn1Keslb3V1CEhM8FJyPiOi+MArV+RnPiV5C0BuKEySHOWZquQozXi0pOGFrFlRSZaMwZI3X4B9Oat2PQdwAx+1gveU/JpfcB9An669VvRPgXlaD3Ad4tflcmi1Zhn++Z7mJ2pOR9YIW//s42MhReyOJC+xD0ROCHa8/LU9Fa20zR55hV0SjOnrQXPychxVSKkDjK7+tD0YDPxwMRKhq0hShicCdxQHa+RoF2EJxiFCGE0ztXA0wwvLxxJeQO2fR15jH02NP5AENcqAPXUF0i7CsspXuOUCELy8zdaMVJdciMYWywRPZAyDgIIDkRPbnF9JmdUxya2kSPLgTjDBwKJXZtakrHeKa6s8AY8dZMm9Lrke8VUMitW9CGccbSLRxV9v3tAuBcsE1tiRTHkioaxHuCApkaPKovKpViWMey0ZF3ghdTNODgBBPymwgnJAmuu9NRj0KJGIzO0AF4p1lRBhSalyK/08ik2NBViHbiD3in5DvVOqECL7rUMGV639DauyGaIlq/nrQrX7ViY/b1WwQSqepM7dgTqmYMb+sPrLoT4MIkku9B6YI/pQvgoMEwYL4mvvk6TBWq75BOFHT0kKhwGFAYBH4cufXYxwUuQB4TsRBc44F9CDmAmSTMsJKCRSHbedmGTIRjkUdRIehUqXib7BAJj6akOlCC2aeDSLuPK3GyzBUG/EtEJtZjA07kAOqV+fIvYT6W8wsjX85hnwG7CWREYQGOcyMEZA+tq+kAPyJ/bFBHMr7MsMgJbkKLs6clsroC5WD8HcBTJbkGNRouyXBeK3IhgQL6cGo+yBzOaUqgkeJZ4jqpjzRDTkslGBr+NGMzLRFWYk6grY+TZCuo4Nmceksqh6Cyf5vdS83xg4ZkGjsMp9SOhci/4o6uPYUyjUT43cQjr6XrjimO66ndJ9WOo8lVtjR7ZW7bXVBKiUcyMUToECi+wklgC0UvacKpz4NAvAKbTSA4A1NgjSOkI0h9fHtxKC7CUXqRG/6V3pBV3x7xZ9Nt5f9ShkYL9WUPMEjDqQq92r2OLijGmf4ealdVSHVxFci77baY1OrkPto9rzN/peH3XRltBGqTHxV2pHXs//Cvt6D/iwvFfN2Mp2xL5W/VDfqwzbFDGCsSmuJXD/2r5UoE6x9vWuMr2vwiFLYUAF5J6BlMJBKrsYyyHLRRwcjUEKPIaulaxd1bOFCBlDY265ZJTic4wj3At9SkfmDL3GU05QrXS5FjZSn7QUoCjuZFVC3HVUnVzJqHMuyjqiD73GgZv0OM5P36wVtfB9QjqhsN1ZuEXXD/nzaUsm8y25XN+Sg1B0M/Yj67A+ftyXzS24dOH5fH8eaLlkxdWUikuLayug4EITvn5QblxrIT2oFEi4Zh3qhg7Dnl5uZdC6EBuSYMApdViCZ4zcQhskdyeBylMqcJO0Hil1RMol+fFqYFJkQFbP1Kp3QW1536pgJJY9oiqUhJlXnfCU7j8hLpgLVUsaT+V75MwGD8ks4tolbIGR+3b+jGtZ0jIHOC7624/+jqa/03wA+IgogcCSvNIRt4ViqenTNn1ye4sFatUtru1hx8rIH9e5xgq2jIOkDYWeEx5Sv63E+YOiINvIpcgI9RV9X+Nyjm/F1Jseh+A4XwC0V1Bc2Fi/VSrQ2rmj4zchP+EofWU//2pGL0N+vtAnY3jWhQ6iD/mz1r3LhHk8szaLUTJcT0mBqVVgxpVnaj1KZsN6XX8Bbf62mrziSa8YGi9gCIHGxVkMkGnU7RV8ZHKpo2jOm1pv+DQyKG+Ym19PoldRK30G6f7uhDGCuHUYha/zax9F0WUMyCkXUD6NQHq+CWXNYmJhHyVKsE/9HvKyZkUGHxf9Eq1stZS8QxoSJH8Z3PpDcByi9x6B+TZdgIbQ0fD2SObj9EAkcwd8Gn8B3fwSydzxHo3AQT5mF0pdUXH0Jfcm5F9VQW8cnUJ548/zxkdEssaX8MZ/5o3v5o2f441fHcFoQlypLyqOZNpfftGFFNGHrrjKyF7Y4A8CeUo+RqYCwotnsWBo3mHrYANlnCksUh/YjO/nU66EVM6F+szyjCuzBloy472DrssQkSk/Rp9XM7E0COjwxUdR1Hjc0HeyTEDYMPSUKvZS27ZJl5flQingiQc2fVdJy9RhWbBnnFn4tBSfluJTPj7l41N1YHQQE9XZTdj29KFyZUqdd3+WfMZ7Eiv16Ap/xnRNgr+erqnw19V1HJR/LB635Zh43JaeeNqW8dMcm6Yj46v9tYXprbAf8+NpsP+Xrtzzv3VlCX0BHhbF92MP8+NHswdfPBqIoVtrsFs36Xg6LQXQjsY0JUCOsbqaB5OtLdD5o67AZ8UtixB9bzejt4j4o6dry0TZE99J86MSCfktIZfVxFK/mkvNj++ESPenZkMfFrKr4bJ2CkGT/zsopCXq/YIhRcoFQPpjRsMCdkzV0d/U4Uk6DpyK0zcHJ3IqTt8cmEgYGR5ygX5T/UKjlqtrNa1LLRb59WLIHlLSROWaqFwTlKuF56h47YuLbN0kpStxm7B+iqdrAwie8TZt/kVjPMUFs6e67AJ2dVEMMbC8tz47WwrWYZ+drUfbfX4X2lO6ss/AVy7CR2K0myBTb73Q3CAbiy8ejz1g7Uep4Eu8YJNeUB+ML550iwOglBvIL4jYbLGMEc2PR8ZJi0e9IhYw3lNX5scji6LVXeDz4T0uMRvCR78wm0Ss5C2Wigx5sE4KDAn+KCBBBVY9Ve0OxeQif/6LoobqbnV3OZMfnl91jS7/As7K3MDtb/I+UuOo9g0Gt1CV8adSV3wSlU3k2ATtY5XlrEiiuLKL98C+rKZ7Mp4DuiMV7I/PakqXRFcBKgUS0CKWqj3M9cfwrfXrg0FmVtm3kQ2hC5WRCqoj+VhSuZ1sLSswZx8VILWwFhumj4FKHWreCaWJDASGRH4t4FSNVpewgWU8nDUwJfP+rJmCJdOzChnrtTkWJ1qXa7/CuVLPbcBtA9N0XdjbU+ztNv5WzF3CdGyj5YpHmb0vMORHKKP259+5Fb9zM33HvqodswivG0oMjrpwPf/G2lB/V0WEl5mil/mHmlKGK9VN9HuCxFyFCo1cr3cnBbWTU4Km/dQ41bp4rcD2t5R3y1j6x9jLkkbcZeq75az2zO5UCMA+Rt1aCjsAHuhMI44L2xmnt4OMN7bCGxjLG3hxnXaajIhme8NDyKmh7tAtX4TJ+f5LwfLgAzBjWerr65Frm/mKUy6R5IM1XRnff08p59+/RDFuDpsNl3xKPVCGuKkEoXIXpt/AtP9ExpDSqD6WidmD7c/8VfR9qst+KMntU+8uRU4RPvsQtAayG8xVd/gqfBEmSyZ7O7694gdaVYvxKjeNqODBmk7q6hLen5tb9ef+Vv2JYP1hVoRQH7B36soSpuwGiPUdGD3lyCwP6lir9f1ZtoK+n1XOv//iFVoxN92og/Tvox3V/P2q0vDv55Ty76MeCr9Kn2es4x34/eTSPJJgxGG1KfmoyoQNkaVrCnU6oG4sZvjgFvO3Joa+Relu7FuZi7U1nJ5irgVyta8YncJ0bQkyPsez8kLaZ/gQ4wOyZtkjZop+tKrU7Dbzc2hPVob0RbndH8y4VRkwDB8n11nGLRWk7FLL6DiLegVOdZk1KpKdj4PHZP1RGTKMVRV941AAtEZG0tE4X76FnXSLQzRoS9nNx6sM/kAK9Pkn6VuCM63qYOyzYt0awfxHYpTBvSjfzvJ/b50fw/J/bp1/rpjy/9k6fw/LT2udX1zMlJyDet6Pr5QhL8OPmPM4KUkfQyP+FKTPRZgccicWKbOOiYjQeeCMOPVMIU3KFRHGTPSLiODvtrF33UPvYox3q9i7esF4p8Kj+nEhfWqJQJ+q5G/V+ax0dqj0q4Le0jT2LpO/U4Z4zwg4q6J6pAjdg6ZBEkFBGTJdf/ErvfiL8eJB/cUKejGMv4A98t1ngFXvLabnH/B5GHte95lARg7ttmJEPcw+hdjm3IMPEOr/HgtkH1c7Q+/fL2ZYWQKsLPpKSagcsBQLyGXqt0WIjzL7wPLcfVKwrEJnYm54GZINZcqsX1mYx52k2NQZsPA1Hcqs7/CIBaXWXHzyKENehN8y68s833tBEBdcBV8KDG9xB6bYbemBKcVxNfE63+UtsXkcsGtHk1ScaVnVkflL3PQZWiHq1UcLqFfbgbF7qGOp9XrsQpm1J++JryrjNndgRMfLyn9ZTX1E3+eITFaOFlDq81Vl1qAJwoaq9bX5OOm/BRE5tkgFRyPUKQhhsvUHymJixRt4RlRJg07N7CjJa+zVdOyxDsRcsnvVheF7zg+soFLq1dD+cDnqR0lh1bKG9skY4vaWCq5BA56AT8Bs3QM/09dr51p0fiZf8FqdkCmIK+PwWMtdSNJG6fo+yVsm8AZ6sgY6oEqKd2t6lj6ffjwcr8Q2tgA8rRd974IAlY5IoS4Ou5fgh9ldm8QFoXzSm6un83WdRT5b9OWfAJh1L0TZdMgSaEixfgl/qRk/LKjD+jkkM2zILI+DtLusPeOkl9irmYvK3+C9VJaFCx3kdFTp+/wpwVLTxdBXPbouzK+K/MXq87m/WGaF0vfu8PK92yhfZi7fJbz8hbWXln/HVH7ItmYBpI4TsJD+YOYDWk4U88sry1no4g6lSsKmZhyIL8IyOolve2sRZiEGG6b06QVkR56JB8NgZdzekihYnTnwXvT2j2L+Sq0LPx1B+W+3zldY/vOt8w+y/Ida57+J0vbkEkviJOzmTdTNqAjuWJfIe53Fz0pDllUfiGBknbnISzmNrH08yzLMyPoFskp9Ef8YzpI/65VCJb7kWbnDjax39CyXkeVj7bzL28lkyfd4ciKvsDDUxgOsxGJewqV/OM0okaJ/JZR1td5OKKsjz1ocymq4AEgNRhn62BGeE+rvbywnK5RTeIE3FMr6BrMEkF9etaQhjL2aNZyNn+VnrUpNI2/Uz9GRQXk1jhVC+NI+aEY8fy8UxBUxENMNa0AmIBP37rWEkOwXaOVFH64u01oosd0hU7sF5CTkr0Xf8CbAFHiiA+3okWs43/QWfMEE++/9zGB/r+h7mbpj1ZoEC8JTzU6st3E1r5cZXm98qN6jrN7OsHpv6vWeCa/XO1TvAVbv9bB6j+r1eobXO7vGqBfJ6v01rN71er1cdGYhNSfHulB5Ja+8U/RNvkiV4/XKv6UE1XnYJ7mI5rN7V6zpo5okFSDf/NkqZi5AhnE1YgG1/xrmzYfxfeSdyJIkARqduBQZ17WpFqZT+2Y1F0wAef4ZXql719DHX2sEbMsLQa374ZWk5PZLI7T7kqnSYKz0BVQCaTW7GEm2yZIN7zd9QYzyw6u443XNTrnkJ3RIT0tZ72QHPyefQE6RTiOkBGVrVCNS/xJkGyX5pPoKdghkUm8DIPFokfyZCxqQgBxDdnmzFMhiRa27IVfttBo5GgOBl1n/BbnXXpvEqPpF6F+pzx6Atx106u4uK8WSkI2WYUt6YEJxnPNn6hlITaPZhnlcJ5MDJr3PvB8zf2LTm4myA+cAHubvHuHvOkOdVZ3Yu5H83RD+rgO+Yw60A+7i767l77rgu2jOVfB3Vv6uI76LYe8S+Dstj71rb2qzHX/3K3/3YWyozbP/ZO++5e+e6Rhqcz9/9xZ/d1XnUJtV/N2L/N2hOIN9GLCOv3ucv4sx1fs3f+fk71SsxywrA97j727g717Beu3YuwB/F83e+SM6o7/Jy+1q4sgP/YEOIKkG1ffQUkZMxGHR/ye0cMgZ9rGK9cc6AchbM8oVeNS8KA3Ij//JDizSRUT2QVjhFiCjTrm0QL0S9pFEkt0r7wkWuefLdcivbuGy6OT3BNppceq633jW8SUsq5/aQy+1k7JK1Pd+I6Xeecga+B4yZcVqQ5WRdQNvC/hRKCfv8jCvE489zntAlORSb1OU6Bsmotp5TgxuN39VRoy3KYJ2j1t0Fcg7C7Qo737R2wgFX4zBgk4sWOVfDwUbI1bxgpVY0KYXlKggHptIo5KQG0F+65Lo+tUtb8DCMXrh/lR4LZ7+B07sGgxZYZRO07BonF70o05Y9JGO2O5uc7vQg3K3vBELx+uFj3fEwsEOrN1tHUPtesS0AvRC6Sc5CsScu6CE5KicHoPuuTJa48WRhemO38QcsQM68Byf3sHtOOaWj3vEkVs9jr1iziGAbI+jVPRujkajXK0y5NtzKJeIvqyOKG7lrxLMjJ6uY0fHT3Js9shLyDDlUWIXQUW3oxjtaotpHCOKsQ/jPPIi+1Isgn3ykZWMqoqLfPbXyK8oH8rmu+QV9lzyQHfZp3kcO3CtZ4aha7mBYAml2kkSmrItrJEF3AdpHHqsxLHpdtROtwGqra9DFAjZ/cguz0yZjm3TO6LPiryNlZgMyAwxqTcouGVfsi0NRQgAa6f4li95OKScub7kVMpluM4tz0+28HwXz0fUiOm0NNaZ0dhUEk+MxcRArFHmS7aMWSpEMc7yr2eB1WbDlgQVBY076fT/fJpTSc4l/gGWdyY8J/LnafDci/gKoitAXrDHkiPXQl2ZT/MhLspyQjI3dxi+K8sKcbjWYpA0U9bTkRHyX1JicpHITQJy9eHHQL24TRLQx4YVtEPlfUCINq1k4nkSWhoBDTnlYiyyfQUeaT8kymoUisEZZxjwWK30qUfOoNwS+9IZ8pwcTEc2XPZe7kBUMvkZ8RVFt7pUj7j2a7bW3ln2XpbMvppiZfw5TGDiiNwVSZbRSwUy0w2aYI9jrnxGJRfk2Zhz9FokiGvjyVfZVZuHaBZ+03wnMn7ApnqNUAYvxVg2voUA4YDxPGxYJ9R7fmT2y15ty5fwrafJZQ2aEn0TAQsOq3NNEpIyjvDf/m1Uukx9YOupTuYxyO3tLRGcjlOi7xMregcDsn2OdCGth+3AYfuj8Z0X9qGgwJQiAkx1zLLbxJxGYn+m2OPIkRjNzosJiE6p330fDFImJIDedzytY9J3TS/cqJu0ltUC/s4JK18E2RWY/XRYaVh+67eYPSYsuxSy38DsId9z/7h0/wnIu7sWMXq+uChfAhy2qDC6QvLvpt90AB/2Wwe/tgrRP4dEWKBpz0eyWBiw5zevDdIn0AET+y4VHI4AVkZ96Dtkc47RWw+MdYQpjQB6R9j7o+qN3yGdq9ez1G74HmbSBjkgGLJMgQphJtKXGheA8lqQNYeVRS1nITesU01JLqTPPIVioIecJGI/P4WMX8/Fp3AD3CDDz6hAnx8spGex2fCwR6BPshoNu2ethdJOOQ1F/JFQ0i2cUk/hpAr8TXu1OpSUo3qrld+j+jSqj1NJR4qQe9pGQkgH7JQS/x2GPdkLWR2jeou5W+kdWi0e/ZZxA7eg/olpEVahZzUtHg5CbfyO3hzS3wDDS5LJ/u9CNQRSIdAZCnW9qbw5/1tzO4AtIJ98eN7F/EVslyvWp08CWojvBRmHWMZVLAPmsg88iTkryOsClkF7GQEh8EBHUlIB61L9K8g/qfXIuj/Qib4JmRsxs3c9nTM/waQs7aMzVMaWUsccoz/HMu1ZxWjmqUL5r2H+qTrKj6EGWf4LmL+9DvVt6nv/ZvqFhFVBkeuLj6p3LGfyx35MaN+gkmnqCUKC/gtN6GoUthvVm5YbeWzDzYbCamdzLu6gVMy98I0pF7fbKMw9HMqVqIU+mLvZnIs7thPm/vQN+nkABreuO457vhC2H/p9LCqILqdtB78ST9N2LLCVs5MywHAV/5MkkK3/ghnAI+QuwD+2jDsIQT0gMMKWOKzURwgqMoShfE9cIGc4jpixVuYGqvVY61oRRq3MTdpNUI1xmBvx1CzzPQkxmdrb582rRnC2cyP0zXFet5cyF5w6a32NYKlFKrqUKN4i4hQkeTlRUDFtDJBQZTkjmsuZGE+EVly5ghgSSV6IhJWT0NTc5cNYGZLiVzeQs5mHiMBYWGGkIGocbC23uHYrkI8612jBlumEYXpW/frLL79I4jeFUoF6Pbq1AjZJHJbruzackvmFRhhGryZOYIl01Swz2XY++jfisEJpsTQ5/28TJ04saLpGKmi4LrmCTGjo31IhegprlrLqdCwVyVO6oyhdHLlD61WHJpmzwObNOA4sHjxqCZCVLh8AjlDMOQfzpx3GyZXLgXkUczZixirMwJMOZ5oJshBLqY98YzzLRbJ1wW6AsTSWh8hJLpGtOZiXAnnRNdFQZCokRbmRrNNDqt4jiPJ+FQyqLUfgI9edRjxW6sw+QpHFfCNY3BuLUAoLrkPAWnwnF2lv40nbRpvOfMdmHEOKUq41nzO2OAFF8Xpo2d6q8FAqvFH7FAqrVV/CGg5Ua/5NavXS13BroMHs2JfofVBLNX/mNfs2a4JFc54Lb65aw+Y2aC3sM6t4fkI+Fl6DmU0sziBkWj/GzNlnaca1X84y03E/7a2z6O2mHTmLtOawtvcsqpjzNTyqDauk3XjO2NHq6a9aYQ0JmlR3f9UKa3TA3JKvWmGNeMz95qtWWKNOhdx3v2qFNXZgLq4Pwxqy+j9jDf+GCwxg/JvRm2LNBcNPARD7u9hOIOG610yqaJQnFBvM+oQvdWV0NVNGfxeATiz4CpXafXYKzD/u6IJWVdW+rau9itUepmrNO3i15ZdUq/uiVbXJWC2Jhgw8YTfylQuqf1kW8qPSAKzqUnuBHLYd3Y5iXzvKNO3/PMG4tH4oRpyWHCCFcUAYVgi7vkAKDPZzX0c1+GVID/Umqf8AfUw9gRBQc58c9RX6IxFZDCRcDOh9BmYniTqOqq4CmCrHF9jKSfROOoo+M4xdLhHUfOgu2VaSTxBMr8ZB1exDev/ih/4TGd3lE255jxTo85VTGWwH1BOlDoG2YP9noveSuvRz2BZPg2SvvaYPSvulltCGNh02Ke5HrjpfjUohXRekK39QMBwbpvrRjp7Cnrxs43hMDSzDvsNbLfeUmczSno1De+q0UxwDasuayNyiPcHa6KC34aZVKdVGQP5CXOAhI9+Bgd6Gvf/XAa4p074+DoQElRR6rwF5PAI1VrVn2pHn5zPtSM1nTHOyJGTMGfAkf7eZ3mXM0jUxD/L8Hyk/M0lcOdyWyyZByztJelg+F4K27KSu3gwMuJHXm8O/NR/fca3XrQp7N56/mwbvsgb1BZH+gjbhJM7ACe0x+GV4UPvTSWKq1lg4U8VYqhFfMCeXmT0VpsRUJ3xulFPHwrN2Z42RAYyYDWvFfYGaVGCR4Lv3VchbagoR6Hd9jqgoqJ75zAB+fyzu5v0UF8skimvrjzGia5JvWvunP8jdHg/rhkp2nopOpYxrZxyrKPmceaCDXNmBCH6Z7COJWP2KvUnkb1AftBizYO9WIGchk34TupNKR2kcBeK9Bf58p1ySxw6q3quqO5bRcl2h+OyAgiw3YDDzIRYK8zEBdSVlPmLL8CwooKmqg4IlK480+BlxIFeT9A073a+1J1TxzquCZTXiNDX1c2Zd7cb7hkbVi59RniTetwM3LfpIqYnL2JbA82A26IgdOjJW55Zhel2FgDvEb5jflFR/FkczjXY2xp5DPTJjbvPXnbSw7lbz2CfqkM9CGEVFXY0y4NgBgZ1ya4K0M5AWRNdeb0M7ce5TIs6XJsm1BVqkvEEqOGCVhDPhptTiA68MRaNkkuSoyDxTfPAVR6EQiPqVvZo8tLxk/4ydtuIDzw3diE9R9OR0lAB+7IQuW8UHXhxaWNLwAnwmuSDwYtAbjHj+RsyMmouxHS9690eWnJ6xw4ZZBfgUhU/rM/oLhXJFYJRQ0vhs1FxstNzl0F652lsYATmuufSdcqdj6+yOlKYelJecnl7ZrqRxdjlyVTBnA8mDimuX0ARLq/TqpzhFPqZMwXkaZcVpmAAiv3/3yMCsvjSjO/iMiotc9nsA6+jz4VJu+LZKsNR01v1F3vuI8f9X8c29gqoi39/5YyYE7EGrYJqjJbMoTT4FCyBg+8t4eHmQCp/bL1jSJwdR2QTdWs4OB4zDiNdQbgWPPU+41MKXO48b9CBvgoWVW6qr6Dnu5SXz9Wd5ib2c+lWT9RNZ20S/l+jET0nMNuWNZjomsv065jM9Ws4wsl/GboI9DvO3lCwNdYGRAqrh5FKFddcViBq4Dk9O8jlpW9PR9qNc+279Bc/4DemT1+MEjFKiou9V5kfj3LuSyx0NoqfBJXrOoDDtKM2sdI8vRUWfS/maZsYjXyDq4ZlcjbVrhi5UrF0qBcsqPhUTWPgo3Y1hjR1DSMIk4496+mPCsK8lM+H82D4Qx5Woa0cpi67FSlJyhcehivNH0uuEjfA6axVNXaZH8q6iacsAelNzPfPoudz5q4TXoaa4chGZMDHa5yNIEa3kz+PYkbkXD1GUsyOg1C/Jy1C2BV0FVzB1jY7FryaQ2i36ymwsl9z/Gz4g7UPjXlikRbT8IKzgStRK3hg7wQE2jBFTlJ71mwF6uxrnOdTdH5jjtXjkI0B7Hl6qx2sJPLUjJf9R3QT1eNFClzLkW2whwYD/D7gd7qcWg8CtsI9jqFjt+yFraYf2Dzw/nrKeHeeNYEcvnYTxUM2oMOzuXC1wwJ3IDdS4WOTHNAi+OtElz7c/K1DuJIHZ7fAt5C+yTyAyVAbPS+xTOEmapMZ8xI5G/AXZNR9VFkT/B6RQTaj/3VhT0Z+B50b4uor+YDSVx25cKfo8GJ5wlj1VEBd80Z6ct+4BYvF+e5ThEc8oVh805S6obkcY5bpoppQdrcTnSjKAUaGYs7ATHceZgDqAcdGmZebxWmDl2FKvoGxYWyJ3xz/gh1ue7oBFv6WB+fhOPAF7YQKeT+iFhFlhiMEjH4DveDzJx0YF+vdSlfdZAwt8qMsXStIdh6f/pmA9BeohBqFIlBh0EUm3YUj86TrSn+ggSAZF9e6lDHfmkedOAwzFRZovDohT/4mE+Kkd7JhxCGpwQVUdE8EuxGf1wDYS85CdeIQ0erGT9gikCZgmOVj5Gc86f1YjidxmjIdlZRJ7kdnfBv3s8j5k1lpqVkH7lWMJq5/kktU04WRlg1MoyVs6V7AAaXKJ96nO7JY5ReuF2QUKb1SJrdmNH2cYU7ISapYZmtYiUIhRGFOAUoLLFkTWXvymXAJ4xFztXD0wmwuX8KProq+7FSNpdBR9XTDKufw7hjGZ9Ed2ev8P+E7/or1pp3daQoe1ZkJ/B0F/33XWN0vjCz2TVcIm0N9ydrqupkcI/8R2hpIG0p8FfwHLJQOWS+ZYDhYycvbfFOvOjQLjeNeyWPhHTQhUx5k/v4/bafYXSs+voHRNx4Xqe+8x/PE2xx91gD/u/KeOP5TYN3cZX8+YO3EhTMF81q1RuwQaGE24wrou73IFZgjZB0iVVnDAJslrOqNfCgBQ51zun+KCvIXwLC/pvAh/dpmKl/k66D4rnsi+ifAFN56/lislb6FAkSVgMZYE0KPZLT+IKKB4J7qZ3cYwZa3b60fHEsGpvIU+ICS5/s5cb96jgssvh1aXboDpiJu4UFX+wfFhfhPHhwynRr7H/Rm0z5sYOKGDHO1M5XwwODzg6WthIuOQYPAaizgPg9wBvhTIBSHOYjkriT+X18NIGiKKD5yur4JRkc0FBMuNkqNSEofTO0hWoks9geWQ84xFH8dwI0OJ7/7T2HhRzdzaemQOKWFaluCrYnQO/hSYccBJ5QJbHTzWxxQdkT468wdT46okNZYS+w1I1tIg2Lii9yf02tc3rej7EpJ849aM+d+aY+2Mh4r/efOKrw2lMrD//8m09ZPUtUv4eLqx8dyyhMtBPn3P1XRStcV8hVbC3tTPwcEKZf+DrxDz+Z+p9vsH08rMJJXX3eTWED8ugslphbMFMh10/CePDXA1+WnOjBVXpsYOjs6IGpyUGSeuHCmgx97gpIxzkFfLBQP1M+gCeuoDk47xWWyheEfAT3RdGMY/xP5pO/EPgs4/PFSn8w9uR1nmXm11PR0HXJ9SRfIADPtO6viA2m2M8/e3Q2VYGeODbZyZHEji4xF8A9BC6EhJaIEaSo+cmitC/MHqd/hsNVwMg+fbF+vwvA9eqIve0XHfokJEfIsKojf4qjK7eatPeRtioDYA/bq4m6DBDkuwc7Evw6e0aQTjGI1c7/qsd1EDWI8i5wR7P5fSd3hZOL/S+53W/Db2HcGggPdoD1K2floPppOdgBNwCtkR4BlzSWPAQhZBjXU4T+QK82wDGhUYiocV90Cn6oAUYqGrWLOinC8wDpnKMPtsShWSWrX9u5xIYwDItoscWkzndSdEcKkjdwMdVt3fyAjqUkbyGWpMuHWrYPDicoML+O0bGIqrBow4nzz1dEW2S14RgdgQ8xFDymsiCCs2hGqU+eJCjnzWSGjbI1RLSlwYWpTX5GYRkohzyT69H5//hjAewZGj5M0i5KhkEW7kJIH0AXOEUI8kgQsRSuw7vyHuZ85vvl+IJVxBZbQXzrKJQqrGNBnofKSw89cpdWjM64Warn6q8jazGPbjMi8WwloEMJ7oZHzXS00DqMAABRPScCsurSMyOYECWk9pwZPPkaLv3bpL15izWbDU6m1vsxWiffEInt/Nr2kPk1C1JZx9P3Je334eRwNsv8Hn6LCmNvt0a1he/jbaoxqwpZQqjIOhna8NBjN6qX9bRFI65xWiIzmvsAMDpbL94rsfFTJDF+GopiCvBuyDwTZwNkKSC8oEilj5fT0JAKlbBMZ24vTNdCl9cgn3RzBeuF9NB/Xkm2zzXEHeD7SDEMSpP7Bz9iE3O1O7DQavFr3JpoNCTbfa2Np1F2lQQSlyjYA+lqH5OEEuF45Z9rH3BpaQHCW+QbfnFBywOpMLFSbRugJSEIc594YIotxD3crtUkHTUO+BezwCULYKqUC1StlN+7D+3BURFI5kHB6WHavl4YG+feqb0Gfty0ZO34wxdlI7vMkR1gaaKxwn4niUyD/g49ztlkswfd8iduLZ1xXaGVbq68OQO2zYfoDhq2cKFrXPOxy91zb87+i97A0dva+CWtouAoFVUfrNASTf8KuNJsI2ejaCAgJ7CMInoigTYWEiLN9jinVIIUg/wGxOYfLrpAgu/EQYdL2feu1bTNShSfPFA1jWsbYF0YcUQBlSXyCwWI5pcn06htWZYE90y3vkCzXtnd7B9qjMKw2kiuwzzPIzbxpxKBPWVwiWdPk8YtfENLmFoibqEnF/Q3LyvXfW2DrvVIRvnayzYVuH8LQOzVrUabSn0kbA6x1YHKrfYUwU/hovvBgryS3iykJP8kkpuZRcOCRHqSSOrGWqvcBEofjAu/X5dNZ4cj7yIMUHNkLaio++qlXMR8lV6BEqgPMmzYo4TyZno2bpSuC9qtBpTCDgQ3gDoHQn16Y7yqc/DsLfuHuef8jLwFfgYCxno9sOgaWusgGs9yFIqloXNHfKMr5HoXUFP+ttLvciljuGzCDBdTU9FdJOOGaVhuAyPr8GfaW054PYGMDv6zAbf0PkFkmYox/Gq8YJu4keYjKukeSdHGHA1IYJHRTmjFHgXNw6506HMHDBsXYcCXNBo3hYY/0JKRBTqU1qCo9P4A1GhOlznQ8zBS0Lj5VygtS52ccnWQRdldv0elgwEeA81aOUlTB6E0aB3gEMp4cfQcLDlZFKn3+g/+9a0rV3UmIdm8iy4h+JwD55C4k6inUQ5Kbs9gQGxznFla8hjXEHvkHChPEJs/K4uLMLd5S5/27lCqAhji3T74AOlP2KvXyD1IPepmBGDLyFdyJQRUTJE0QfOmecXejNF9ibGRskeQdwVgugIhFYp7JoHtJNp1zBxRB5uzO7mtHeo7aSxqm+u5Fck5KzpPG39cX7G2eXZ82yd4SdgkywMzB6mCSuUoeiDxATeaK6ueUPQnKGU5mH3udIZg8wEp4KX9euDOrBl7OLJ10aJ67Wm2aBTreXHEViDo8YmgT1UPlL/A8hGzrAOBrPNI4epkT1mgjQ9hhDPJBNrU+EpzGKtQDAA57GqmsWsvNev6BSnE/yexSxwf6QkNm51vuMRdDeaTHb+b6AsiMUey8WH/jpAI/XY8S7lRC0o17jJKhmDWn0oN5kvV5nrHd7gKP1CyE9U4Z9NNZdFuBoXdsH71gXxhABZxlOLwGGwAxBv7TQCB4FVCxrLvkAYPoXXkE4GAgk+/cFsDXeacYDzI2zC9yOAtGbKrB4bjF0MRzu1V7Mi5KF3T2Lh+qSJLmkpHGbxz7QLZ+gsH9u+Xh68q9uR4lHHKmmJx+v6cLjujw9nzPKmVM88n4KKJBhH+eS69Vv+RTsyXgYQPpH8hnEY/qAetRP2bvMFz3yYfJX8yjzIxGw3A5tuoJeJxSdiYLtyuV0OxC6SCVpS5qZSQbQREYpmZjR0xwGbpSXSIMFkBeqBTxWN2IyHRtArCzUHm7m5mk3nisnSrzXnVwQ3kxYC/cEXDGC3kzNj9AnrUsz4XeKRxZ/iSHILZ93jsEDa8wUtDQUYWtVgFS5x7mC2y0Xey9EiP6LTCzvvwGXbjHz1MhjPhlcP8VdIEH8rKDk4kRy3Fhj/4yOg+U56S36OCqLLfRqlv12yHfxWrWsFrlTAgq3CSybaesWD+Q1bsMmksSVi5kvaBYum2937hLSjOf67HT27K0iydsoiHPvvAoI+1C64gfFedZo8gZk2iaxEi/eCKwtlsD365M3S4GouyhICImkeaG6HvvM5HISmGU8V879CtIKmOh6GE84FaiRkhWVCdINFks1zFwJzksEB0qKdUrPw1QUySuYZJJxhW93Rtf0wBQrsqgpVR5ZlerPupO3ttYMkkbQI59Uk+eT/ZW5VHtbMB5JhO76VYf7c2yA2edQC7GOnQH32ZPwfNxeGZBYJNmSLtQvYjrdvM31Dxz89L3iJKn+gDR5PtVKHSYCPj0WBbPRmaMHY5HJnTawOIsJQUydF8ilEzhlWYbgAwvXQKxXlnHOqSzLOGYE9frxYF+06vJidoLH+q8yduAqNmvIF2V0J8AvduDHGDgi+cTi9RUF6jUyU1mS1uN1KOkDnlFmtvtlz/LjHyxkDw7Iw3/VWTJqKEL0CQjwcRYm0yO3qJtyuWB5nkIpF4m+O1B1JZTVbHcrr+gkVX3nVWIVj1Mw14vILC2i+XXLDR5O/tOBkcETSku4jnhHyvobADMgUzncMhpzFhXh6Tb2uxTG9iZ6NrkDwwXUfuTedT2bHpp02YvzWupFvo6sWTgU1IOhnqxUsCiJIfvYy/MYvr8yzDYArOWZeQzd/e5BTrReHfYqHXsJPLXDbG9QB80zlKrVJMl1zBzA51+38qAHWZTZyjOWmQjwR+0IzWqftTBmB7cbmYVLmYUPLWeJ3NLg4apXqWB/uzDTmaMAMf80wIQFKetDxmHGx8fpB+ngexau3FrGVSzj2AFXVdB1L3rBhVzliWtEuhj9he5On2oxm/zgt7/+vVRB14J+wvznlU8IsPWwhPjbi/+WM3MdLEqnEhO5LuAyJIWxcyyh4uKb+T42FaL/wwjGCNbyCF9ZFLZoHh6Twz6i4ihNeYeSAdegdlJljVSppvmrgLUuwmgT3OCapnzAy4hQRoMy2KhEh2d3A6YqRwf5ROrDGtaHNwq9tYKtECRi6EGpy56C4oYbyZXHnpi7yP4p33Os4/P1jndgaykXiP4swCVZLPgg8FcVsWyaWbhG9hFJ1/gnN2BHaYyoZp/elU0GrqfondeflSSc6Ngh5kzuyj5NCyQ36OBjkInePi6Sc92HGUo4lsD2aMED8VeikKEvN/BzRbg6zNzsv95OeY8VmVZsK9p+9Dje695lmR06IjcbZfc41BnxyEckF0qDFhEQil4/WaBiu0ErChNSQOLB0TAmaJWQxTZEPvnBV2DfqgmKVIxPyjCDU140ElGDW55fhqjBLS8pQ9TgcbBQiGLO4Gso9Pd8tow68vSyXSFIAoMtp/e0gMtA0z+ILYf4Rr4zusC8zYwA2OQPieCLjYGUiu3GcVBdSFGjejej19xZl6JvAdidHv4BDD1HNhaFuUugZmZ/JE4fw6/GykE5Wt3e/LgzzA/Z5EV/1/YsmcuSd7RvA+q8Drpj7P3vkNNbL8kbSYvYqQu7KrRHewZ4NOLA6CQ3OlB+nUzeFDPnE0sgyadLzmcMqwZ5oaR5ez55+tCxn/yzLjEv3+0oF3MeQweOwEvVXk3I6JpSxeI9FoKQO/NsuaMy89xZcU1+ShU6OwgEzL0E02d1iIzkaEZYwWZR4OPVZ1XfBPrs5qy1suHns+Gn4CmjlYv4ErNp8J4RjJl4I99WCHtzB+24M8BoQNVEZmXFI/3GbvS/GUK3euzACv5hgsKcybT4rRY7x3czG1QuMznaxLlsLy7iw1zEhulVMXhlJKN75s/IlVJvvm+Rm7/vGnYc5lO63C0uvKwBA74fu5hQhYEWGpJNCKU3n2h9AgcxFkr0burOmqpl4/6w7x+YwG/tpgn0jQte4k8F8Ay4GI9ho/ZG0r+O56vI74R7aWB8xUQev5G2g5yBMkMGOjlzUFaW8P6XY+A3x8afmHpkeIEnuYYdqeIUyhOwR+JzLbHNllyXParmduP8CsowZzwY0juonsoxvI/kdbAH1Nlz9MPE17Bz8GsNrJZRgm3uoK3KZjJNvojcCuv2Io5qdTbPxcbawBO9QgNXiUiU6oCmQ5C4qFAHIshBdgFIxbWFTrkS0L1si2MYx3fHjWxJcelWOanBMqStuPB41cFMSelZ8TOG2MiPwDNryzlrnp9cKDNtddZqjqWLr7cYFmSXuHYN3+eMYkqDGO2b8RAuTS9izopxdRjRZsOu6bBQCswUPI5TM64AjO6SW9AfXEpuUrfOYfJfNUZtHcgXluE7PmMwVoaUUxIZtVtO2G0NLaGY+90VWOaUGPgCH4R6nGEcM0kUxDhx5bs7MCqIA6xKrsC2U8lJqPGiJI6o9cjvIceMsE3WI9F30I6dr0ipQkzeS2eF8HwdN2dzZkdcywQhmfu0GUF1GRLG4887QhuqQOLOfngeD11m689Kg1iDond1gukEophWgdarRD6H5OGksMVLSwnW3I73uQBqLFQY8lMXzOba3Gc6o6xSJtB0D2IbTvT+3DmEQN2B+PZITwfSm+kJBL+lq01U+e1zzI7LCEPZ9EUGSye36PvRLW/3JNdReA7iTXu00+M8jZ/Ft8bf8aPyTlhvj0zi0hdzdDuW3ESBQzhzyjCEGk9qAXcgqh1yH7RB8eQS64fWhQ6CGdi7b6c2eD3v88mX4L0Khve+uJYdXPzURCJz2TY1ULPO4TqKRO8R5FYQfZAeNkQ1fRsa2OSwu4jizxPzj34wT3UI8b4chZ3FpWe8UOyEVQIhM9rbgdE2HXKQBe+VlnIC+V3G32bY49zy5nR5G+CqKGCL+KrcdHMIR7sdxTPuxeXPsEexGPKAPlV5FgeCkmvMhP6twnT/iVTxrdLUpDOi/zpC4vkUrh12qttbanM7fp/+Du4/9v2TqGOVQEDmrDLdVIO8SC/thQaz/uv1n4AJyyImTGFx9yTvQJiiyWiPMnipIhYzFYsgyCmk8HuI0wwbDWaT6KV7ZZinC7TwgcVgAUXvGzRLxAai2mZkJWqpJLdj24yXgQiy8AOBhB7j0DDuST6tS6J4ipck0TMvkVtAK3rD5VHA8RhF+O6XuDyK8cHcyaUZVkkoqtnN0LPChWgZJqzUuE9oAp2nm006t3l5oe3ju+08GnlX8LlbRBCbLteEuDqODkw8Iuf0GIeHnF37Jj2upluJt8Mw3co8DDaCsErSWKB/pJS8U3Jsk8RhBVrlOdO6zKeJdzti7KJ3cQszw45jR84wXiCTYS3q6pl8n2a09m8DGfaWF3mcCe0hPX6PAoP4BsVj7iViWs/MJ6HPHh5JXutCoeLUR2ca8u1CJt+K/q8xds8fkHFvehlk3PvZ/VWhUThoFBhH1hwfuuYFPh68E6X1eJ6YqY/nQWQ93sqXHI/Z40AwS6oQ/d+357LSsGREj66eFh3rZM2yR8GKZlzN5pUxHEd1nEX7BOkVcUDyfE63gCHRMQ3gfwcpUzm1erPw2kKdnnP0LvofvRJV+dh+BXdRZWzjzefaYhvTk0K8Ps1ZiC1NggraFwh9yQV43wBy596p53Azbha94/CMykqGdGo6LaR4S45G0ZcHjMJd7TNPScCNZ2pSYKSAVIvBqDb3nA6HzDRySS+9eeyqdz/5yyoM96Kt2k97ODAiUnK47IliTg907nAwCRrmAWb2NmBl8n0gFQv4yjvLnmTJeEZcgLdJIvJazFDBYzcx9GFWs6lznv8/qNd6M9EV/XCSxJzXzrM4bitMIurpqziqsq5cYaKH34DUvjAkn+6K+A/yaSYD0edXhFAjmykKAgCcOvAbBXLhxOwNlixpEJtMMa0QmkGEnH2AC6i+h1FAxT1WTcTWtx0FVZ1ZZWmzwPo9us16XbBrUGc9Fh/HCVlMI2zJHDQqEEWncclUCwDany40G1aILiSzSUFQlMe45GFFyCKPBZZSXJkPT/3DJ75d5n+ZeM6EG8KzZ/IiYyVIXobVcAtVJiEBxGXgtKTeqPwcktsVQz980A55ugz7ONG7qJ3FGHaY8oFrGbTXa3X8ZBW+b5sevdhipkcfc1IfIkaO1sRoaRgxesNMjPyXEiPmkob06GkTPZr/SCt65OETqT6ZgZpRsz60Tl07g9Mfgp/kogyrWyhF+sNhFtAAI0GRRIJcOv15+wWC4vbfmejP/c0h+tMG3QmjNbo8QscN/3d6IzRfht78EE5vXvs2RG/umc7x8+tt0Ju103X8PON/oDcZQ0zf6P1tuF724HOX0cv+ebqhl+WU6nxzKJ6q+tVzBr0ap9OrWX+QXr2QgU5eXNzXlQAkXnrfOQ5NMZEGSc07sWxyqy0hzjx3PqF1MwNrqN+YLkHLhVbQs7W1loDrB1orBaaQG5rBJ+uqwkjOlUJD8i6QwjyBmPaAETzi8I1EKj4FGoNaq38moS7ojaWChVyim04gYHEpmwMY8p1/ykQziLXpGzz9rwvhK7jBgX1aSY2pr/giCkPQLSLMYsWIUNqyEwzzTxLEudtAEvmJzED5KKa57JNSqtAUh3cOySivQrmZQOUqD6OR/zDjwjlF1tWVYZRZqvyaHZARduhEmoizQdwNfepVnUzcPzLQj6Ho4vBx7UjLtQzMdcJHC5qzumMIQYfUpmv4OvjC3H9N2nizPquiDaRWSzOgfXCM70cXhz/YyR48AlakjwWJbO7YWnSk4lI93lU4Mx1NI0ycD9mSssjqM8hHKE707j7FIJS9VNBw5HHsFL1FPN9GcgBAxgbJsQuQ3BYADoAKfJtcyBEcQ2oYOWURv0uoErDe22MEwwSEWoVq0jaw4PO6MsDDZ0B9ZGprRNii/vAsR4SfdeGGoch4bhj67wqqvtF8/Z46gbwO207aWxeRfzTtKi2qwSxL+g7HXqpeNG9CXdPIv6eV1GOE7w8wRCCwMbcDS4Cn0D0gybPpXd6BaIS7N2BSA2vpxBh2FXlT7JR6e+wDdT97Sd4s+q7sFkKnktyABVI9jvrpXVOq3PV1yJWVolKLovwQnfpTBzq90V8QffjoDtwrSJUaSNCdEHipMzkTunPbnb2Dmah168COUQcSDt5vGPFQLzROMi0fBXH47hlYpnwDpA2va120XcRBnZ0x5supHp/CF1KjhWSVRd/LuEQCq1pTZNBpxWbM1EA8SPJgLPWamV6V/nZJdJUDEydLQr7HcVLMeb8rX+knu7K5lt+5DKnwmEiF5SsmgxO9krcD1eigrnj6MuSi9xSDXDQhXmGrsohRjoV1Ol+M4ydVV/KZEBbeUtNJffRpTu+ejGylB/nwWa4HEX14P4RHqG1D4WEob3KGn0Saahg88e5eE0QiiNc8OXFhmE6Fl+TYECtfWkn/wIwbdG3QjO66Mk/0bolo5V9E58XdcTSPk74wMc1f2ZixLs+knU2Xf/dw1ZBb5vFdFetfvzAx1fYLeOfbGjsPmMk0oKLvLVqpOOJAfPbLsyCSktAFmuM8uCYBpQBumvHgBdSTIGJMY0ZYv5Qc5A4ZKw4bLY/4NroqmbPkHseaEEu+y+0t0lly2fcn4shh/0HF5cwkVsGY8vl8ljG91KSwbBeFixsyzw0M01U1c6KzgyN+bFNbXaPDFetqOCP7FcYhNhhZdAFz4nGL4WicyXzWoLmclZUcm2Y49B2fcas+x8BY4axdky6r7mS0x3jEkQUYFC1nhvk+JMZf3gF7X3PiVT5QTZvXEuKXcEANJv5PcnQUvXhhpmm/LfycWLMuFO/8nkl8P4xpQz5fO0nn/+4Imvi/r+2hXW0a6j0GB3fRuOcXt9AOE/DrNtmQEvSuZnYhFd36ekezcX+S0d39n1F3RabHfO9vDDG82bqvXXhff9cyg+HzQebvaKBZb8SY4po5yglgZUZRtD7HsBvcd/Gv6NSAvkcJj6WTvMCPOkkhuYFws9p3EtJKM/KtbX0ek61+iJyqk//GOhqPAsX9iHWxQM1WNr7VE/X7SIvR9+C2P8LnvjY5GKwJeDh3owOpRybaTjTyZxJC2tqD2isXQzyLh+vzARH3nsgRsUduDOHKzMm65WXm78Bs+HcjihSlHUDkrpaUnp0+FQxljcRP7epOONrpo4xJTOXyHWm8/9fzu+ih5s3n21/8cdEDuP0hhahDqPQ4dmT+brQts7bJugyZ5G9ibGk37wWjcwbeUb4lYK5jYTY88rshSFeyLcMZu4StI5VbeSFsXw38BK2zF4l+nZtwGfr19FM6/eLWDuCTtWcu0OKGbJVcWNDFlTDzfiuDq+4CwHlt7eI++ED9rpDzDDnWaN/sMY83TifGLiUuDU8b3YLRzsyCnWLRdzOOdG512Ejv/VhX9XVQO1xupNkTWgt2qdUU8ib3TYw0hHecynjYSQ/nqH17NiQ96Cw7iEkmzpz1ODENRbUnD+rqKdHXux2A0ILRBxmfvFh3shgKGbncW8CsL0HpaMv4/6QymbwipKiqP8B1Vd3Q8sDUVOoB5s9glhPDVqnV6uh6F5PEwcVKzbM3tDAefiqXZIZxHrmfoSvqiAxlhOh7gZszGIA/Zh/ogTkcTfEn/pM+xnAP0hr20qqsEszEAp3U8Y7M+CxJqEp37BC9ewj693qSS4GyA1VsR2YVwJpnRO96dNipPImiSO9FnMqcAXlkG8kjSA1BHvE4donet/CYk7wDJVoH67PozW5goEQQMTeC3zsuKQsZcWQykuj9BFVng7id2uvBcw198diJvDelSpu7j01/uGY2NtJkNTI0s9u7hgQ+wpptSYW9wtdGmwKzRCx8ZkeQJVIAxLrEMscodGPWZh+nMENmPrgCAOQNzgd7B9EhPw3JBcr7K2n2oroAzRG9vbCXlRr6Ofbm64ikaGQBmqu8HSKNSADezr/j7DGl1iI+e8172AG6VCEEB255XttctujbtCds3779gb5vO6n3j9MvOtlzKeEvGacT/vl7KK6MaX2YgvmWKLY+1ZSaCKW0H3bjFW+kmq+MaCX1Aw0NE/YVNvfacypbyXBvl7TYkFmQmwO1fgi4FGmjFJ1oiJMW6iQHO/YmegsP4WyFW8vasJXd8zsbDyK9m6JC+DwkleuSXq4JGWYxFkf0FZ0PTSjgeo+8G6Z16PswrRbOSQBKrH+CocSrFcbkhM2uOvkvPEYBYH63vJsOJbZCvSAg3WFatn3/JA6og/r+E5fBtQl/aY1r/VoImf4vEP/o7jbUYznP8LPD1ZaQqeVyWhVUOsznKoAll2Ai87ce2UkRu1krIScYhHetbg+3lmZHWgwSpHVuxjhRgIgsF1j4SDzfyWXsE/DoDowQQsL1nR3JvQD5JvQl/aWJHIbpLJT2YS0b5+U1fJa2NHyf7UD28BM24JBzCnrdvtqudRbFDjU2ok3iCkbJEEG2tqcgyv5O7cMn6acJNI/yBnNICn5MiwWTUKzvYzAnzoRyEOEnJ3x0mFCx+qAEj1hhvMEIFerUv9DkLfiR+bJPes+kns6KCMk96GQTcpLBVU0yuX6EOcmYPWcu7yyjIR5SFiaxg9e++dvRW/xAlJnPIR5GKJQGLcbPTo+VHLn9CBd0pOvI8+MwINB+7U/sjuMlhBrCvPY89kRXLhM2tIFQR33uUUNzfOsJrjlOFwxv6v+Jox4CG047jdg+EE9h1DR7I7LJ3IqCyj+OcQxMQ2hHRzdpqOKRGk2OG4EZZkPezzvCvKeZ17RWUoUVDITLUGzXdiafRyCuOdqhEOoMeUXKepDsEFSRgSfMsqOd2cZCQtl0x9+ZtDn6V7Du0CQOxV4Eot6iYT/dyMyUZoy8bgfbSiRAC0sMr9M8S2hDhMwbDHioo3FhLlde1IJqe3fR+cGJzGY6NzoUPiWjo95YqYUkbxZe6TGAs4ArsR06+nIXYKODLnsKLgxRmJcB2ahPPWLAwoHjHBbm1f0xK0LKYwALnxxHKsN8obSzF8xQveCkDtVLuAML10ggVOfqUL2YQfXLp8xQ/cBJdg+kfFo7up8twXIuNBP6W1ERAhMOIx9W0OoEyE8BuYVFBy/lFrIwmN4Lx0kY1/3noMQZYDVmFELtaOLYHkD4rjwWxpFUYNB2Yl4GkG2jvOYfBrvROwovPvfnGxwYxkIA6Y+FEStw17MT75KjARopo2hkLmorJ6edWS/c/zyL5cLWE/avO/BQpOTYLIkjNlMM0K7nTWyeUE4rXaBHtKRgKBXEgL2zkDQGFVL9DiCkeFEK9kYCNApykJCP/BW8FNMLgFNiRQ3G2WClzQw0Z5pTSLu6mN8OPc6I7IVBw7XlW4iPGBWI+YF57VeK3rHnGHEafU4nTv6gZhJ28bMhR33zJzkXz42nY7YwUTzMPhgyHYashGQyDDkeT8I7yK2vzBUwYDPNU0qV8yfj9F2bcY4enosnfdfQVtPJykQXpyWcilAcJKIgfR9hFCSmkZ32ZX6jLdz5iu9R7SRP625cDDEtvgyT6n/GxvBW6iUm4EORLBI7yHi5vzWEOSC8FNlKqFOFh3jkRtT9TmKyI0qBX2PFtYZoV3AsUpq8JiTeIdgcIQlPIFUtW+8KdORDQQgjNUjJW4gyw44ZJA2Z96pgEec91MBPPLHKcqXmagiTsJG+17ewLBpRP9QqnItiU7KD68LY1KwOZ/5E/5+5Rze+Zp9uJdQRWqiqN+OfnXtbUVWhsKZn61BhHOeIvq+wNEdLx0J0hdDT9J1hXvaS7lSvK0kZDUFFA8XPArDuj+4kY8Wcp/axwJ2TpMpPOG7QccQarv0skMTh5RQkn7wa2Gt0aXA7WkRvpGBYbxr4FtyIdscCskEmF0CG94LArugTR5QzZCDsBLyDtkj/ekQMnuR69O8UvwGE2gKEO5WXqpIcG6bbJPIfrT8NHSMGcb2Yu4Af7Q4kPOMIMVfQfim/RYfbWCj86V1jWqv8qi+1s6CeL/sBbmp5NII5D1xhWFgqDStY1n6T9B/JfOVB7uc4TcdmhNoM7pxwGyE2QG94RwXitiIdt+mneLSdv7fNKoUpmsxcU8RmgyBit986FTrE5Ek+jViHLsr9y+FWx+vUeff/X47VMYDW7rzIzmBIku7+67hS9La7GCa4/r6QJKBO6pI/can18IVLpVbxfl1qLbvA9cgmMWDVSYzMjkc6ldfCJpfIhChVoidw/U6Ck0KY0XK3/FprasF7KLdlJMYrdPV9FELyjB3Tsn8Noch0uZpQdwjFP8Z4ZhNXHe4HYuau43TuGjH+85XA3OSONpgbvESLmJtlzX+MuRnzAMZobQ7RHeBGtVzA8krPvlkChjG6bjSf+RfrTDM/ls38D3/SZ/5R9BpDB6Z5eNlOlbb7V13e1gl3BXffHKgzl1Kgf5wEojw3CUx/icKHrrCEUKCO8cxEJfU/EhXfp2fCAGjJAsGAFGWg+sNkPPzHMKsOiL4zDN7pg8mNkuP0jNsNrc10NKFUakaH2lDd3BfkTiC8Cax2DfViA/tQcqGJozB4tNgzIY2O1t24d7G1vvL6+/4f9tiDOwzNzJ2nmbnF0Mzk6qciTOoZ3Qcjs19rLdv0CZeej/r1F4Cda3ezddbF+cx7/rtjQLTGThn0M3sBpP4apgvXCjeEp7f+gs4z2kN7zO68bLsAb6QrJVod1mLbKF2u1VybwuCCZGWm8SENy+D0y2hYvk/nGhYdBAw9ESfGfWrRn4GA3BuMmtOuzfjD7Ng5P3SeGmEcOk+7D9HSK3GmKMO3saxEI7hvkczIhJrI3iQZb9gKqpb72NBovcYXGUhjcr4ero8MtpHWqRjzWclj9/qwK310Y43MD6UqeRZ+Dn25+Ww7Z1iUPP2UOlMAzcJzK3kD09jzOHElxS9O9QXx+Du7DZXOyjvFt0panYjH5Ccs6QqdaMeT7kNz+bkAOqj+ZkKro+xJ/Cg77yEVqkho+zR7P52E55lbwIzLnGlnpdVOOUxCYed0w4+3oyiCx9uJoxlZTsfbGXdToEdGxGt6e+JFO4lSwDOQbt0rl+rrpeRKnLpy8z16pvCX5Ub4y6HpbEGX6eEvfREJpL/A5SbMgHGEB9IVqgyXk49HwyiOKjD4BkMX5a3MG/OpQrh5I3TSnZnt6KR7SfMcH5Wlh2puVlvMD707eT6GFqSHpIhWx+C5zds4IG+chtdVhTq2lHP5Efgvc/mdo4N6fpWLF7D8EEsY0HR6CyuYD8HTNT14Xzeq4z6y0N7sp9toKQT/G7cyvi5LYOEw8VedNgo5ufD40y6z39MRPGS2ys02fiyycJJbKK7ZjX6TXd26nfYXtNPe6oK9gUoUFnBWJ7EzmZZ1Fie96ol7gsGa9+i+V9MRbeBv5uGlsIjn+usaSPOx7Gn6ceyFpqPguZZQSUl/mBR+kptFervk8LjpYLfh+dFgYz5V7FQ5uZG45VJPYJmF5iwri7ussVBtF+eGQtk4ysSc/lzjSavtbQrCTi/wKIkhaFqOMOFW2kFpnZEV38x3XlsAItqCK8hT9ay4KN+VVI4Hq8neBERxLDmzuQKP4o09/bgYjBh5dZAuQz5Uxmg+Z3Em8UHVxJjkHQGIs28Rgs7kChbMZ8CzczH28opuWQRQA/4CyfuUr7vRmB3nZ/zdlXxSPyuXJq782opXpTgd5+f86T5lUTcciMtxhORq8b4dLvG+I+n+qowBLi52umAPk6HSsQ3e1TrFe89gHDrMgh+Sp033cYGM6X84iDR5BadJbNTo6Lm/HT+n/Fh7Nqt5GFlqLb9MLCW/5qpLQkE7ajNieQAhkPO2zzjlVtgC+VF1FPg3hvapdXrn4q+gv3uVAeEkP4vXo5sFnWvY1SeCzkSWNMIWx61D6gQlarG+pSbiEUYfe1hhn89wURbpF+ozSRmNMTfVUxK5Rdf6TA5HQ68nTd9cpvc7mEjdewYVfdZyKKc9Rh4hFkfR9CvknckFGMVdlAYtKs4nRXrPSGLxmWOc6syzZCFXoOleJsz07y0QdEMCi3jEKDdqOUayWBQrylgsihV04NypLIrHoIZlvnmW0di0JUteBI9JGIerP0VfKoYZlnnCe0hE7oicUnNe7mSxjJLnH8oXQsfCDOuRP4fCaFtPeWFgXvJ/NNx/Aj38ZoOtrkcA+WE0m06EH6bMqU0XC9ItSs/FGXQzsH0aZ43c8m8errFBf2Dsecj/eryrNWMzjTE2u1ycsXFDj5yrEbjyMGwXThkyV04xrcgdWIAAgwYQmmqFx8OGr+CvXJSSL+/kfupxbsdv04cAitiZEx7tyuZWusG7GdeyX/HNQmf0dmCSA0hVdJjFAuRLywSl/QCiFBVpMLvY+gdqk3meAdfvS8ylCJFraLIc7JxoRl8oOD9HYAUwXKAgTWazStsf+B/2Mmsxxd5lASmHK74FRB2U2KQcRMZ1clH2QQpVyQ6sBR4YhtCTrvTojEu5Jgpvl1x1dmg63mCZTPoa65Fskwde366Mq04lz7tf4HV9tgnwD1wTwpg/xVm4V4Z1S7Z+WgKGifAFMzSy4CekHvA0rMCrCh7HMdFbA+CDsbYUZGKK5B2mbTHjJbP/EWe+yVOt8iI7csFgdUnHtmD02o4mzZTCOTzH5hmdDC9Vfw+r7oj2rxHoWW/yt0IlMshAQ4LB9pYXcrRxF3V5hoNMrZfQjttRLOYcpKAR1tNZPEwYu9WOAbyBaliIdqa/5NhGiUqkTAq9TlgHfsOQTs5zxNVzATeXezeT9fVpF+GgKVnGUiA0j2MM/Vg6+XVACKGkzG6hnvcSUvK17s3cHm51ZDFYHG1qnn/UpfRJrOlE/nU1qa3jx84UWBTM7GFG/NiwDtQEsH2ZKaGQ9MHm2qwTQ073ToSTPk4czRSwA/e/I/qXMVOaXMtoX+z0ORTsNYXRvoTxkExX5t/GaN/6Gfe6ktf7188e6VZW3MYo3X6n3Mzo3H4QzDP6Kis4mWPuqY7T8KZCvHeTi7ucc6TAvk/07QUetN1M3+jqMh87KEfDEH3vRdPZedrKzKok+to1kh6DTEyTy3U5hnQikbGfzxYw5GwEZo0mfmWTJ/AF41eycXzaxiYOf7VuTlRmQB12955pXbnJy18lyn9vz+xIKLV08JGkkjkyFMTg9YUuswNOdrh6bnlb6jkxfYskG/X0WAgm9UVplhHYKCsU2KjwFcFw0FF6LDb8H+9ujcezuP/jUENAXWG4Wi6j+3ecbUQ6CkjActww4BXm3siWjGFC9IggIA5MBoy33+YuOGxzB3rEpAvHa6wcT8fbKUrTcOjDECQWmUddylcUF1ixdn4F7xc5j2tVO8zr68dZjSg7KUOfupIKXZxl2vSMrIW2/KpLtvwwJWoZWSF8+vULYfv9jWdCTMarqRTvWZllikLf40rTjrZDr75O4b3iA3mpPR3vwJjauv+49ZFZGA+wzzIWR/D6IZfbxz/dzfcxfDUB6tR8YDDCCjPNVTQhV1IDAoTk2AjC4k6JT7Hk2Cd6vyP3hB36ceZAwuHrcFHcyQ3GmQ4SVwqGoN51CVtvUiRN4vsJfw25Za9qG8IVzxe7MR//SbSV9l+FSvCiml/1syQI1XG6j/BT9UzWzBLMTsTWCS8LBH3G/RvdB3M1YP96kxqQw+CCwboasFs9w+UEvYMXowbr9aeBVtxxhu28hSbTUJrcrDNsFIDQFUlG3cpjab5gOvqVplVIoXhQjPGg7cZiNrD4zMqPPPoTWoRrPPy+RRQXaKIrVX+dri7CwFEejqxSYGEqyxj60PmvXHbO8HNG7N61YjMeDGfCIla4cqfYh6CC4m7kf1gYo0bcNFmWkL1EP5qAbD1Tq3FXfOVrfurmgG5soiOenuQqSRxWgRqDa2Haf30RN//yXBwSmkXG4cGL5HrJ0QTgsz1MmYrnr6CbizsyezH1R0efXsxVrH/7Ozsq5utyLfNiyu4YsrRJgZlJbscFMcdnBAz6lJjJypLzGSOrJblFDxi0rVsoYFA6Bgwq7IaYdmS1S97sPSVkiCl1C72lPF5QPYsXBNjCI+QbUUlC9rsOV5D2A4Sx/TPRWbiiVhIL5tKAdSOco0H0/g1dtoUKOpvaIOZcG2PqeG+uGYkMmW1xrdPRGHZrDIX0ShK4o6P1nplm1oz4W31FPjFiLepuw7hiACBxLEZCeHx8a8pMExdX3p2dzeQcnDV+ps6+tcW3NYneEYBhHUxygEQP7EeDwTGJc91ia57tTshJdzSLOc90CbFRzEoY1SUU5ssNbKh3dqz5MNG0WP2ELEzk+Fj8VBO5B7DDY/IYeyr5VEmxdE6Ga0s4HnIDUeOYB1DS/VcLFjXVAWhM3+ytTsouGshxzjb9gFhVDB4QK63ZrnPzet+Bq0eaq11rjmcSOgtHJ/K9LzYw/MFevslC0Ov2oV2i95EGxlIQd5q8RXJcgDHtI4vt3WSxLeLjIPXPmz3RM3tHOD59biAO52tGcuRilxF64gAPL5R/p37oDc+6JReLvrVX0p02NVvaRKGl59pEodc+z1AoO2+x+w6OPxefuxR/3nunjj9foskxOAaPvKwNb0R/l/ZMTsMuaCl8Ppmu/QLUVtZRQdj4C6xmz0bF1JZXbys6Plxy1ZXbrO3T0OsL0NDzp+iCDdx/2ug6ZpFHrkcQ517dlStfMfw8aliZp31yGdfArjECn+VTBd8/jwFB+Dudu2D8B+KvsQR720C0qhuqvcdtI/lcqdWPWNs1LLBub7q1wYPOpHwxMG4fIlzsOiFo3NvkdQQoOymEetdwa8A+/e4EPMLZmxnEsJ+0oui5tTHC7BiacCcK3I4ySRxRhtgqh6FnQIQfRzB8wjA90gq+KOJK7IW8wqAF+OFUX1D0n6LTjdYVM0xo6dvYkKE2dOBzPg/ApDfyCZ8r1k8Nlecm/Y+OWn6nE3i1JtSy/xJxcDPOgqNezFkZjWeWouwIB6OiTVpZfYc5GmcMMM4s9ZaUSI+jdsb1GKUF8QkjSuixs1lsdT6NiYlzB5LQVT/dhDlzCVy76ohz9/T/hDjPiDnXsQvDSSQum36F3HiJMugaLmaM5dNVS3qrOWzF48x8N2fn8fQem11Xcq2jAj2egHE3TpfpFGFirCVLP2nGRTVYpUo6TkJXZKypZGojn0B3Yfhe57oiZCpiSX2EWeN09ZErMEmAjgPOMUK95XzdFXffEtp9LgCe/vxAQZbp2Ee4nL6aAdDHzwkhsooXO/HzD47FCJ2i91q60TeoxR9j2IFA2ThDnWZls4NTVsq+hkLS1c+ZoDI6EctU6yc00+Vz6fIpt1zqln9H/ZX12udMq7okzkJ3IOnLGvXcf1rWA6L3UasJaN2d6VMmoH3C2hpoPVYE2qNijr99a3rYvX0rengyykwPq1Flo6QBe1QterdEMSbMRA9Z5BciiT9E/VeSOPQKIIl9bzOTRJATwqni7BROQeRoThVdUZwqms9gEPJCHznldn4GA+OPMfPwCwI7dob+ZRNi9FMYG4AzIrZWQ/4/lcccYJSIxb9Axz4X1S00sDnGw5raKYTeR8k+A9330s9BtSmitnaD393YJqm7Yyojdab7fGpu5fRuWeOl9O6Jfjq9exXeegYtZ/7bO4+Z/ZryjnO/JqGwJtbwX/roOFVg/ksex3LyW9qvvX+szY7981nWsU7qo3p/ihsu7c+mW/X+fNbAbx6v7WD5HyfFX37lpVOrfdvALouaKQWitto4W5uT3Yk5ts0MYzvzLKEokBirLEl35aJQ8Ij5iat/y2UfjKHJuDUWKQYLrTnGbkM/lbiaBAolJhe75fOeQVPsNtgJ3WkeMp8x7dVHe5L3iyf5gNvxC3CInYjbFdeu4B5DR/UTdGrprcw1gthuXP+unej2aHcgU0BLj+s6j31wxqt0PCMQf5550C9i44lcxIPjgES7wyPAdhtjnyl6n8C74Zn/9MCwqZ1vBKBjg9vl4dH00FshiUK+e5QxGC6ST5ghU/i/wevNhV3/i4Dgf6sDYzez2DmHM8ybwCDgqEriCI/T8NBR6jh+DD+LO+H0wSUWWNt4UnmsiXMyzHjim+xb2j/pSIX1wtMh9Y5LsSNo5vfhoNl0xASaTM1wVL3/Fv1qy91HGCpPDAuriSFoJi7k8c8A72h/xas0dCVy2+aTj0gxUcsVj+nyEY9cwwOVAPTQgex0udlRoEuzFCQJKjC7ioMtgOhTO4RoKguhpJ/xqWY3zDiJdC7iHnNrCtgBbT5T7N69AiShyqJuREEXZSMF9TiCYs7BDhSGAVonDR/Il/IG+IRukxknpDvOizkHADN6CwSQ+O4WZFYUauDIYcQFSG1lloRFLs43M+5mGitwCBc4DPK1FL1JwOlqm8/TeWsXc/MyT/ol/M7bsF+0SuCZF3ocg0Tvv+rMSGm+jpRsIJbjrUlh8dJW38yBYGZdK/yEuqa+vXUgeKSO66FNMsJy87Fsxs19HoVLWK9dDcXTHa9glJGGNjHky5MZhozn90bcrvfjqzbw5Gc363gy0NBKTlka7pClE+cMdxvfbG980zT+5MvoN2/j3/w9XT5KoUL+M2j/WBvy5uKA3Kis4LzhJwaqJY4m8LCQvElh9NNRKo4oRZsQQLjHcUT0HY/lHOAw2XePHv5rLKH4+RsZIAO+AHy/kSCYexYBX8jZQaimIDTLFQXV13RkTCHLQ9jdKuagJMCZRVdgpoDIqaUj3TtJeXr8sFksfti0UPyw4WHxw1z6fWgshhiePPEXX0HmeT2IWJk5iBhzDdAnmLxJPNwNTV3ZK8zZLLe1s5lHZzomz6fautOZJxDT2SOXh0UNGx7DooZNE70DY5izo4QodnQW+nWjfWU+05w5uP0lp/IqRtRYyIpNHP9m2Edz0UrX2/DVNDAyNqwfjTRvax0FI67OAkSvPnyT4TDpqeMOk181XeIwOau1w+RMpnPGH/V6AEetU51xUIfYxvIEdiiSjSPlTOgaRIvZa9EI8HyjWWQ3MV9t8xfkodFaMj+INM/Rxy56z5xoc2N/9BTbZDwO7KM38n1ddKIN/udGfV9/esLY1+yQet5l9rWzjU/eyj8ZM3GhWnPDZfbzkzca+7lZs4f1fY3e0JEJhCHzaroZ+OG9G3j/b7zQBn6MvVHHj+3htfrsDcZC/6byhd4VeckRsP+40HfBXtDehtpqUqi1oH6I6HjjHwOb4wB6WsHxUECnMA1SnzNtLuG+8Tr3+k87H33EmUtXL+4GffUOnb5UqQJym1veBq09B62hCSSJTCDaGyeDwZBFRDt9yHTYrfAsmiYqdD8qrhJ1J5eHjBUDO4Q8q9Srb2DnlOJIpVaCTvJZQkht75H1sOQrzDYLj3xMHWNnfRfdySUZ6chNYYGarepX1+t+VuvbiofxHyd7DkBDzRvYoUSTlOOR4/SOaI+fgt2DYTnLSAdOHqn6KTKPY+/0ntpDGGrTfH6iVEBPJd/dkH9Xu8xTbh6fc4SgK7m1bprZHs5PsL57kJ2466c7YJESjGL8bYdJFqrSUtZrw/AosOOAfigKMLXLVp6LEQd8g9uxuKVcVnfhmZg3C7XrNLpwCq+guhO+oM66zoDR3jUcRm1WRk3+u3vavbB+2tm2Rag//zUMj3S9jkNih7OXQuLc63RIPE4QXYAuj7qPjPeV0ybF76XHrFEEiGNxJ/z+mDakVUN78R6eOh+K9/iF+TuMDeeLjRAv7n20V9kJ1084XmNkBmX0Jw78B320E15qT2smBRMwp96/m+9q4Nq9NtndpXRIrhfjdVcQ/6ssusLE6+oGMDOfOz/E30ZEEH/LWVvtboATzt9ewvhcCchFizh++QL/wnMQb59k4W6I300u88h78VA9k5b0GIG1UnI5GWHuxwXDuP21+iAlocGTvFdy1IreeYcRfIs0/OXB/SNDjt5ZLFhAFxQoftGmnmYTyI68HZGS93oCg+82G6yx/L2BqLslucmT3ORBZevwbYi3UBYvjGMrx8KATGBx2vjht5pbyQqHYaNRWvrtOn6L7gXYN+rEaziwvkyHaK3PPhG6F6DcTFL1gDWtDx3oV1cQHG3aZ6bacYZqLpcI9XrR92T7/6orGBUb0vfpHWhT76fT+Qs1l3yUUKgNPzionSmykvxjq1ACzjYo6/zHOWXtoLqvbm3Z1qnpuqu5ZTtdPi+uZIvjZZyqkGpDrsyQkBZwATqVu4fFEcW50KZSXA895BJX0uVvHnsi4/EEhkDThTLzFGjTDrSJkNY/plPFeT358u6tuxQXNfXUcVF+nWmDRxrHEun4cfTe0DlNQxEgrwkDDG3r74Bq/h9EAb65DYmg3BV4USAFcZhAsJcdUidVMRcCmGBb6M0XvAdE7ngIROw3UjHtOnv5zb4cTwAT7TGW6sX2egRoZuoWc26zMazKAqb8dT8dFhlqEf0P7WcxdsZZMmaKCySeSgWRP6+TEf85THzQY26TGDG1Bw/Kj3a4qnV0Szs3QhlEub4eg+0YQoRQi8JDKobZGSfmbKumM0RDDiCyeo8iO7LTAtC3CVYW3JHh54esIW86j1wl9Q7tkFCMR9+eThSoLBqZ9RxnFFOsTTI8rLXJMJMof12B8cv+H+U9JVzUQ9EOV9drP2PeyP30bqL5cTQLb+T0lgkU4qgKAy7Lb5q2M+32r9qhWkNSYsseEUIeoltCW8THr+hishBs82zY5k9edbltvuMqwxGN1fDv1v3a0uWton9aM8DQM6dbx4FhYQl2tzMRXVQwVx5Fxd4FHQno+CK0+QkT6JiCByHjaOISjIB3YeFJP23FGUY5JCEUHotUTRP5rVEGuWWXR0lcp8UdfssYCYZPK4s6M7JLDr3aJxQ8l6sqOeNhvuIjlbkAqFFXUzDdf40VCHT1SDFx3AMnkQXT1Q/stwqqexR6rfn2ksLTbIPKMys6L6fl5N5ubegys8K0n74l0aja3C36c6PJtUI7dywUpEr0/RJtMW66IDebmEi3vEeLPRYKZYT2B3MkozoxZ3ok1/imUziWM24E4VpzQAt54WUkw4fbUHklPCyYNN5bSPvVQS274nKgOSRR962Sd+kz55a3as82mnpNRwq5x1Ug5g3cVMJ6w4KSc2Ukt+buiTCbAP+jqP2XjswhJK4N8myo9pNqodvs/iNB9H0LYJoemC0gTSSclHNFNHk3HqflyX0dI2tSh7nw5OHiVCgAL0ONeCL5QxsJV7sv8kMsuoSVkq+uuoLJdqnm23i4zMUFKlxdNoetv5GOV8Vw7FxwVwgReeSBehuhNlm5UITczU3GeCNEf0GT6XiwrIJs0lsw7gHCmA8YD8ItflPcdjwI8gB+Af0X0BqX0cS290K+r3LploLwaBCjUVktVPObIqVKFVAjul+iphrb94iuau6KCd9G2x5Ff4D2Idctphen1EmyF+syrC/j7VSAiOibMgsjpf3thB7nUgfS0L1lrfgP9xid/2ifwPmPP7UhC72UoPMft+NbEvmm7A6FVvEgE/0+3s1C1nTtHxR78jSLHTZjp3ECdQ7l12LosGTVfO504kU6d1qz0jhPa+iZ0BummbxhQjqnvojNmw2/bIzOVgvNzSiQAv27UABkXSFRKnp/xbYrwz63in/u3VDI3gshjincSqId3oFIbyvS1Jvr4bs31dDpYHYtvb5nRddpj4JbdyXs23RHhZhTpztg5DMa5JG/agPJEDH8FfAXEcNV9wsWM9inhq0aI4mQTaaBwdnq930JmMnvT6d7IG+ioj/nWEh+D5khG6tDZsgbww+NtRVfYUO1KUIgj7NwwKBKLLjR9MowVvnrcIL5xwjlEq50/BFvG5lb06ZxDf3t/rB9TXuP4gwtZ2T/NGe1Bq3g3/sBVjjU5cfsUrrcZBuDrjce+2gtEakLD5HiQRP21RpC8TYpeZMb5FqvqKGC6bzWvYXDowcvsCrD8wblUO8OydEoei9Q0NJKqfKUJ1mDHABFwAibRO8Bgu3TNZ+2sTu/Gs12Zwd1cufLaCCrO5uO9IYZbf9+xmyAnrzHWHnd4kx+FmwleUCfrsdCAX12anfsMYd9+d/kSlRPz6hEUafULVfqWijtnRMhKpPZHhjzIZaMOH6wj4IROtRgkDaUrBsAKBTHdSrrAuLjdOGQ7soDeNcjDq/mATgKuBmAYm8csZj56x0UPoYOzOqXpZx1iz//llwBaN17UQC8XMgu+BYqJPEbHoojFIFD/GY7ht94uqpdWNgNnSDOfBkQjIkSpvKIG265DAngu8xkHDrBWXHe5Lq3Mo7pGVPNNC9daGm9/9XfbzfTuH6G3YLREE5A/iPRSEO9J6caMK/axiOk0Ap17C5zx3qaOqY9icf65F3IiiVsRS+c9doT+1mQQhJzTcxg6135X7ZkOzIozudubEYz/2v1zymukrKQEU9jFi4XByMFvqWY6OYs+zRt6BGKkByahtvPmaahmxjSA7fmJ7SH6wmgOVv00hkWj4BCW1EENG2PaXTuwIMCRff+QyM0uOLMGbpWlmtYq/cxfl+PCZsVuiN8vsHs/xgbDHJpVRdeDXnVLKyC7Kr7VGKweJBbtZpaU8BEXSEcvwUPYKTL29PwfnPAi2SrMogBqwg7X1lOKKdO9P1lC6KcI4BySnXikWAYzB15DOX4m3SUUwsop88WHBndXyChJyTwNpsznvHIGtP29sYr3+UGvLjARhcXsGsLcE/WuZHUX1dn5mYP1iI3O0JwV6r3BQa305na6Zl01roOACh0HKwPpLSD8CcsGFbVeRYMa8N5E/76mkBIEw61YRDnq4HnI0cB7h6cq4o3QsOZ50zgIlci9/LCeeOemwdBKPv5tCnCQii8QjUPsiV5g8LsaEkZQXfaS1BBHCRYgnGYGijJRROk8cw7vhqVzZN34MEVj3LDKOhEuv9Qxh14AtiOukI8suS/QD5Y1sF3YRMTpMioG3hYasUSkAS5w7Khoq+elcmDMu5ATA/8VCkdrp8gKbx8YFE74uuVCJSu/CXE71sfghplLruLyGXgQzoyLdcF49AZaKxb/gUbSTI14muXwgfZz5S7pJ2Fx4rpl4UecwjBpTSxs90Ck+bwPiOoEUM13OMXdSJeZ/BCf1DMfYTfRjTQLfyKitUk8lu+vgPnce/CzTT+QbLzuXGdFq5K1JcPbQhfdmRU9VfJ25Ao+jtySpfFBJ+F7BqmTJBC1yZxwWYpH0Mv/QJHgF4XRVkDcWdjB1QBSYEhx06xj2Bp9Tx+JDDkMOSpjhgeMXRdHN5Oz2NilKmnOyIAzozVFVvkaohNDaigpoasxtpfdWT+WWMlpT2Ss17EVAEv3AEFhDhSca9KwGOwQJDxnBbGGOhGF3e2BzZ4lUU/8sVZZDpegTdbYVAfDKTJB6jFtkfX2HREkU5kxU7gAsFX49wK3vIz/R6Y0L0jWeyDTtL4rmw1ZLwXy/xtfxNFdGweL762LArPzTq9JUJ4UzN+cONMI3aH+SJhCUnqDpHZwhOZ9UcSgC7PeAD9A+UxMGJ5u+RtEjKGpVTVXNPqUkYzf+vYnnENcGZxkrdQYF4SE53eNR5UwVhe3M+agt4k1rrFgva0qnidxPA0didzC0Yu8fE+5YtyDr+Au5fbMd+OVEj0TqW7qgqBFtVK4rfdtL+0mO07buUKPlimbfqRGrB+OoIDdgCPH4zvCqLQQgq4ljsLMn5iofAkUzgExTIREP4nJggkNMnZISQCwzog+MzuVMcOAQqi/x78VuCpHcQ7mY7S4WzhRrkaz4ldaMf3yUgsDT1RrLYR5m2SYR+nzrWxPVLJ9kiPFhY1bRzMxDQdYGCX3HeCXNNpo3iA7MbxXeKyTzJvkWXtEfMD8zOk9DiOU92OzSvwIWyLtETrfv2F/fPIjRRdqbjLHwi6HxZ/vxbP00v1R/Gp4FikJxD1RjowTMn53vx+krclWpK35TqDL2xz45VVf+9K3ltAaDzJMHcPA71qulqcO4qyW9xI2IFslzRPjf24Gcn2kWp3cm1Jy9TUasmrJuFticUHXxmRLxQfeMVSUNI8Z1i125GfuVdy1Iu+AdRIOUrNtXhNtdzkTj6THhgWdHsbOolzG8nmVA7tFRe8NDW1Nh34OW91bfGBFy3WO5rZccP+ONHOukJR9NXQIax8l1CYnlyYLm9JD9wPDTW1e/52D9Dg5NMlTbOdDUhfvfsbnN6D7amdTRexnW2sHdFHFzAnlwsbxJXTYO03pOauiGFLKQVpOuZSoJtpLYFRguldC7yb8SzkNwdGRZjymzH/Ici/GBgVacq/iPl3Q/6FwKgoU/4FzL8R8psCo6ym/CbM7ySulBoDw9rlzo/CbLlBinTZ44gsAJojDLv6GPpXtCPMquDzvnYcs84Px6zvtCPSnvsNMCAgbEwTcz5tYlh6wLFjhFrHYfXRUExbSidwMagDuycEcFWCOJwd/jRolrPU164f+Z6Pj6RjoLQJG5/Pxy27XN+y8TnAuOGbVSyq8SK2f5WEz4fh7q/K6FRy+vn1JY3PRuXA6gzBy2hegTfOnwUen63XRNThfU1tz2b6VCUqh98IYYRKxsBjE0P2ZIZs3I72Ys73lla4+CPdE2FtpAmTkL4Yp05JsML3s1Zxf9taG51vxs+KPzKs4t89swMgmH8Tc/TAMiFThNRKTGX4a0bCvLmUr6lNwy/vvQj9/iLzfS10LhH9A6N0/5fhdCjfAk2uwTGMpoC5BsnPWmMjR4SMkdJ4HwUBTqkCHog5oSfc52TzmchDR7mUJRG4dmiU8N8TbWIdsOmk0igb0jOtd2MwCG96sDdlEYyL4RfEK0uuHkh3o1/dn4WMdCEJ9DYIz99i9p+8JxDf23TlpncNnboAOeFKG8W5zdybLu+9NzAhMejMPoJFnNmH8OdexbcfdfzpgX9bOkRZ7u3tO41mgFpJyEazUahbBiZEzIMhV68iNkTe4ZGXXNULewhdk5dEMGTND3XKe4ntHRT1f0Oa5ngvcj66kAD+xCfCnzGAP9d7kssBf+aOAESej+cMvA3RL2yRHGdFbxGpos+QOX6XFHgJUGgQUOheyt7ulk8j9nyqgaQnyXsUEGhj66AwpkcDt7q9+WbcWlzwypxUQK4Fmb9LjibRN5gEk1onkIvkBuiQO7khPTAaMSKg1ikdEbWecSc3IWodBqi10O09wFDr7nqGWgcz1JoPqJWs/ckVaUJlenJFemAstHKh3fMD3EKTJ3kb4NURgFdLAfcDXq1mePV5aKT4wxe3+eIZYv03IdZap3BaXDkz6JI3peau6c+wGyBanKX5hFlntjgDzwmmly3wcsYMeNEMLyJML5rxxZ/hxUV4EWl6cRFfwCafeQFeRJleXMAXveBFE7ywml404QtRXJnaCC/a5TJiIFd5hKbSCDqTNhb5SwkoNCKG1f0YxzN2lBKvZf1EjFHGsGHKim+ZGwiTEhiwyisS4y14+B1fjhOGKfM/xF9k5r4HXhY3QHAOFMKzNqEtGbDedwuTb+JtyK6k5Jt4FcDNiw4BGokSMNTjDe4hnG+ajr5BiN9RSV6m/mCBrSxHOh3F4oJkBIXF2oEzGK+GbL7AAgnhLJCBL1OqmLhJBaK4ELy0FXI8amFRhHecoSjCiAgTRd8GMvElVA1myGcxcW0uWa0Vl7+KGDRzrpLw6WDBcI/AOAlQ7k6812IwRmzBoBjIPd8wTOnRC1CVfKUVWeViwen4bQbGVpkKxQC5RGHMwd0w+kf7QjX/IVG+Dj2klBtG8nTulTCxNZ3UW5tbGK6NvhTXHlU/hLcM1x5rMeTRMMw4MGV3WRS72+ar00Ak+hGFYSKMRspLLs+krF83gJ9VZccK1EMtLcG0lHxYDVydU5GtW+btSkrsS4MEpivfGWmh3vtm0nVfG5w/dcQIc4Ex9iAgmghgqOUK2GCBmTaXY7NTHNbohI2es92GFq+MKYNSRN8jGHW9sJ3oS4OHQc9Fib7b0ITVECHOZTk20TcRcw7Aq/spJ0b0DaUyURnJg56LE303Ucqa0X3Qc/Gibx6l2ov+GVQaVrkfHjWUC9LkA0CoN6VUOZMLAQGNXQ8ce7ZL3u492lBz83/AX95CmwSYy7Ed4AXE3JLzz+OZ9SvyM464hA1yxaD+2aLvXXgRGCa40LA0GoYnlw3q/5Po81F2BGVfJRjZz1B2JGVHhrIfouwoyib9IsseStlWyt4ayu5F2e0oe20ouzNlt6fsz0PZTVbMtlH2wlD2QcqOhuwZr/CsCsrqgFl/51k/U1ZHzHqYZ31JWTGY5eJZ71BWLGal6OOnrE6YdTXPeo6yRMzqKBcO6v+66MMDd4p1gEOgc14XLgSD7Ort924UAOoLgcVrRBZPGQiCxzUXW0huGWjAJmyiuoEg7UTZtPwLiC/CoHa0znaIvh/x6iyd9VjPWI8C3PY9DZ7Dx3mO/IzoWu/XlBAuZTzo7iy3o0T0HsTzwMkqqgRHExshb9KDJ0JhF+lQOK9nMJ5ljN2z8EASpAoPLImimxXlPSjUdeN81/WNLdyx0r8jksmYivXknXhzZYsu3KkLGhlKqEyXD6IND6U73wjyM1G14dC/7E10coWhbE0C3tgYmvZ5HXe610adCgYVhmiccq0WcRHDun90J1uSSVDJ6b0oiPMmtqBaUXsY44eg7RQdFr2nBAzp5u2Kesj6nW6ZKQK0SH4ft/poQ0tra4iFrCFVDazvvysJQ+FTWhE0q/Zt4Bhwb1MbGPCDBh0DrjPi7Bh8fvjKl/po5QXgBxnikqPs6NNva6VqMIR7VArQnQHHWjPdT0eiAqo9i1SXUHSHYDHFjyGuIzx+zFImO1D4mE+YEXApkxv+cgeCag5x8BRU5mumAljG6dTQJoTvhNQ7TEz8E5EUSoapBHzpGE56/BUACoPuwCt22dXGLqX/Qt1PtqaOz+B1Og2h6AL1ao4+35rNFD8Lz9Umb2K3IaCJ6xbSQo9hUZ+JkQ4wgcAMucmFCOAIwMvYAJZzn0hxofq0/v28Fr2rAwcIhibNAN0tdaw7m5hK4lWj9JMDEMZPo+I2jp+wh2UzNAucGBOtVvosrOmgNp5nEJbAR9uCgkkGb34/F0agHQCQ/jcwGcHXD4HDSdpKctcY72N+0rC+/Xnskkz03kBz3OgIftSfYwplTQQPc+C/KaIt2QR91hKh5WPHuFqOFFRm3dxzZ/W4P2zjIg4ZS77Twy+aZRqFW8tkX4+BltDl1JhOZUH7ltOe9fXoT2aai4Q9tTJyMmrSjp8PBuUKUwfH2AfKUR20t2DnIzH2eXFvB+Id2m0gSqWQxSjrHFqOqrSCc7o6qfJ2IWzadSkFjQpjXYp9Ydh5qqfPmVeDe8ceOaevRsCac71Ah3LGwriNkQbjSqMSBS3tAlNMjaU1Z7pOfW8mlzNNKek+CyRxRAHpoy6H8F9oMSF8k6x58DZi90T/LS3ozN1C0623EGUPNeA/jxDZXtvUqKPJbECT6xhPxdex3ylcYegq3QEKs3aMohqVu+Ut5uXOOW3GuxuBEXOW8jDsbvlXuv1olj0OcfbY0+RnlLGPAA6QbS7GVbd2u43h4j3nOC72b2+gGFuLtdVHoXvk5BHfoke20jrVE6aOoBwy2l5EZI90RjvRrI/nIHbkJ3r8HV9TwU34GhX6WjHegQXdI8Uy6+B+DUOHptTBSJuPs6WK03qdRIjJ1/qfwOao6gJszopPc5oZSF7kfi7eYMScdtTfovBQ1XIL2lLc8jndnJLU1YhW/Q6CT2DAR3spLLWbBaWnw2WSuvsswNuQ2n4CoMd3fPYfmZ/vGnrgKMzpbYkUfS/1Yd41aERyBkZcTA9MsSempdSlByYUJ7mVxwGuBwzcgWX2qXPP0geX7qIkzPyifGd0qToVsikBTL3NGV2W7jicWeLKXWH/gXvBqBSuiX0cMR7ul3U4WNUFSKqUqVrQI/RKbpu/wQLC6hBLFvrusbfrLNVQvAS+5JbLiBnvnMxtF+uwOXXXGegbRU7Gl8d7cU3yulim5uil7jxDn6og/RYacGAP/3wrU/SLepSFRazAOgvgkZTdJMvUqffBV8tc9j4oSFFIX/K2KYbHxzArdMtAGYs3zTma5aHHHfwxz4Ku88l0UxJOyqiAr09SZPh14ar5GotZ0PHq0y0sekHZjbgBd92I9fr3grHsoa/mffUl+xcKUVx/BM/86C2Tw2LBMSuFGpK8LbeKc3+zY7yv82hbSUyXj9TM4XJT1hpaNPgMHmZUGHGia1j5NRUShm2m8NKBhN7bUFZaa2G3pyKl/rS2BTDsUdgJ+eoXMN9yGVoX2l/Bjk9OI7l6muRlXeqH3sWpovdWewiFlzTNjlNSo0AyKS54cXYFnyZ8rqLDoME5WQyMgAUYHSTrJ+/vVVHkg0D9DWJslPC+5m5t3dfGUy1BjS4L4N+WlGlxHmVcojIzhvzRmNPdStb83K7o1XmIxUrUQ9ekpWAQHrR0yxfKWFeJ+5a/Jj8N+ArgBpQlsS15L4G8J7lR3VTLV/REIg5Eu4ocFLH6eHHB0iSKEIUax3xLyOVIv9ALw+SdSaSu7eFhQG8MzZ9LGRuDY0AVYe6XZPOT4lyDgKyIgbXdmZZ5tEveIRVUW8lYznqtpMbgrrmnOwM9zHILv3iUe+PcjvViTlwPjPWxf0Z7jzwxLh2GpLBqLmW0Da+tXZBAtkqLi1/T55IrPHoE+4LqKHcgxtKKv0wfZBNzNnPaTajHe0xIV8bZSpqmumtd8mib09skiAs69wh5ZRQXNM7ezOKQpuTX3M3i3DoybHEz3NL4JvyQVHA0yiPke4QySbnT42iZMRSaa+8KPNZFKGmaY0lz7BIXVOGkjC90j98YGGOJkAr2Q/cG26C801E1Zzm24pJ3YSOOlukFuucY1LbBBIhenxDqskceFyd5NZwQHI43JYi6nCXGquWZhufO3m9BUz7Gnx0NLGWl+Nrmq0PLhktmPAsT7ONKGqemJun3RpacnrHDhqMvKGn8rQAfij3oinhtgrmF1CTXoCn2x8TAlz0Qk6cLaf4Tc3ppJ3qgsjSrtf6xaWoETYn/hOgLJpKCxxWYFMTxOyubPQKswTF0tvIIZzyDOkzf7JGBnwKaPA6myjr3Zq6uuvEiUvCsKOZ1dsOzmM87DcwYP1gJ2NHNj8/kIb50Okqc4r0lTn4RNaDfK+VCd2AN9w6qw8/iBs090RIkOYaa11YBE0R3JC9GFgbmXfux2dD3GC5+coN2H5p95SqXXA4tJUnRhW65KrQ/Um0uZVxMSctUKQ62RR8xMLYbCN/3CP7dc1za5m4Wy+WNruH624iSljn4OywRHlIT8aBAty6wzXcExgYrL0hP5w+Ud0lPVw30CA0eockzqMv0DR45Tt7oklPjXPK4+JLGbaNtUFVKhK1cwbDM1J4s6ukedr1fBYul70exDuOz34InDnY45d3YOrSrX5CgX8cCVG2Sjh8zrlvYSp6bxK+zw/oF1TAxFWhN8W9D7ZwyMsbprRHSlJG2dOVvidAuimiQHccd3OExXmYdcysjk3SCBc+99Lsu4LkfdmEmTjbbBKOBOZ1WoYzd4VKkPTjn1U7vBdjWJfHMhxK3xjq2oV384p2aEbgA9zlcNw2ccb80vhKHappGJSLdUTFjJM5/YFa0EL4GTscFccG3SJLHF3jGHw14LBHpTx8aeE8g/iao6HRsnPM5rUsjNAbNTP8JQxAwRMY+zs/uwzpJ8jSbPBYWSoqnNcJj/O9Esl6HUwb6npchaUtGhokOpOzWHXFdeHcRKXAYmAKO3aMPXacPUvJO9YdjnDAcsiFml6LNhOF4TChmgkvBO+wQyT8VReu/h98WVYSxE9DxcMGGaOMFGp1GM5S/Q7/giKP8p6MZytcDMTD3t3vjPMJBRHg5J22IZHfOaC/JT8S55Z26a5dL+RND/WeoguBC1n4WXtCUYe8nFRwExFHUGt//HI7n7wEc8yeO5xdHhwCC8HxKPk1Ozd1MHrzPkZEUN0OSxp9heP4Iw/OlHuWOdMDzQ6C5doFZDM2jCLdgN0PzCAWA5t0Fh6LuCfRPguKI5r/FRuQmaAIqTy/SocDA8gsIEf0VsHuNgd2H0+UAOEIFR8gBxiNvlLIPWsjbbHSi5NgyO83FmWmFEWhJ3smsksmViNSGH20x4n+5OGssyWMTL9G/hK7GZdcuPmYfh8s4UxKK8IxYObnSvAUtc6x/Fyp0Aw8i1hcXPMtXFavW2NvCX01TBQP/R7RvE/9rSBw9wmlpUMr0zXpr0FebU94qyf3Qj8nO6IB/io12BGPMfPexg3OfEODvRqh0tyOYJ1F5BSEhOlhFofC8jM8ZqI3VEfxbLUwoCvPnrgnD9/qSSXKtltZCfOCPjPViU6pzfjC4CM64hrg/DNHBXE4SJm2EWWOMJa7O4cMtKMblQyFVg5XSV8ifLxeJ8o/slgN9XMCInetkGsClA/SjayDi8x/Zfc3EsHG8rh07Z74PtBUikuQKbeoFk/870y0I7Io4mrzVV5q/baIAiNV9N8OXoZO6wKN/XMs4R/ZofZ4kfiWTRz7C4RWnoVP7oDF0VPr43yMFRMLa61D5vJvUPwHC2uwiBN0yNEtJUK5jWhGcfG4ZGgWQMotqfs3GKO8FwSplNwpe9hEK3s57SJRvBtLrLRIcW8hE5LkuZCLag6wwVpTPKgm3dhUoPvivwDMrCT15Kvsqml/zUAVNPhuav1YQACv/wno21jMHQ0ted7j1khcLbc790MTLzL32RQM/n8evHsLA48N3oIDN7rHeS/szH/imNFl1w25LF2rdg+4Qc74Jix/p9J4ANHmvDQ27EjBBzYAjPwRMX7yfcCMxwTXDQuXvc4y5kfDjBoYfcePWwt71KJ3djibCj4LOBjsdv4sLNlo4fjwYwo8xN0Jxp2Mrx4/ABddCZcCPjk2IGt3isNNurxqH3fU+SoKTdVaSQId22DVL6JJ6IcQRSkrPx5JCHKEkew2GEJ5b84Oyly4M44CJJo7VrRjCFw6Glkf7TjDPF3QR9UvQQ+op9FJ7MGjaXwiStbqeNsCEO3mf/jH150Pmhc/sTBwMD7L22vqYsLKdD5CMq35R3RK8DJrWz9EDujZwPKLtUtF7MISxF8aaMHZBrAlj3/bf+U8z/l7Q8f+Iv9dezfn41KawVfvs6j+4amjtNa+YgV5g5dT8/aHJrfV6GTeP6kP003tgn27P8cVHIbbpKPo6RrXB6Phm4fnT6Ho65oL7jZ3NvemKS3eiSffCNmXLOQpSohoBxoqkQWzhxJzJeNToU3J1L9e6YRiZh0DEudtRKAbe6RjijQLDBHmEzV81J0FblhCaf8SElg4AHxWB0TT5lU2S0CBX4tRLQqNn0LXTf/PISTjrWi8eSznPRKfWkU5peEwqx7yHqkNzJcmReZivPVaHuJxlBpZn8aueR0vyWWCErFjthLkaLugavJJ2ln2svCuFFiOPuwBggWSQlY9aYWmAHSxTr9vXQgekVKYnG+vSFQ3oIK+tPh8MAg7ifNETDShZ/TUOqbR/X52ZIQI2STuKOY5NWL4TbkUETv+oRHJ5fqBHK0Txa30YyN3eo22QKyP4YktJwKf91BxWsan7H4ZV0f82wtK05hB9MPgGub5ygv0xaXwG/AEuEyd34b5WkzvvCjIQ6Xv3tTfqUCVegssPG0+rRGBy7JXEYWf1EdMWVy5F+nhZGvG3beF7jDNF+F5Xefy/4Pv3/v/B9/OvarWMeATGtBpTrvqDq6GVkH36Uvxdk+tl4CqsQ324ugFWQUujw5cHcFX+3tISJN7kLGncE667ihkwfBbhUsZksmI9c2UrxiQfXVYSDl4ZclmpIpeVm9Fl5Q5Bd1kpRn4kYc2VOj9Slblb6flFB+A7oJgT2YOe7/DUUzTahMVXMs+Zl9roxZS2e/F4271IbdWLO8J7cT3/7ivUi848NUQgQ/tYaLoXqfvkIpDHrG75nCScdSuD7Xi5gVVdtbMl6PYWJ3kcBzM1wifq5zuRsgXVD+i3Xn1nZwv5LyeREl1dvLsleIkjk34fhbKztT0bhyjvUyN26fZs69REwaJ9Bty6+vhObg1d12KyZ/MaFTtb+EndD1t0e6DaW6/xXhs13jdqvMJFB/XCjsv0Z/pOoz/7roD+LMH+/LqDt17URuupRuufhvrznl7D20aNTkaNp3h/kJ9vOcE8jRay0FhqK7ZEHbinBSNrh3iQRZwHqRJfKwdSROuBnMet8O2Q+jehk1kL6LGP8yjjQNBN7eWJlBL1vYjHncalC9V0yluzGTzIQzEhXeFg7e0Yjo7+F/4jpD9s7vBf9IfXof4wifSHqag/HNGN8x1HjobpD2/pdqn+UEcZ6TwqhDtMdSj6duFRZlIyhxSIcqF6D8yVtrYGCVI1hjgSh9eGIeM7atrkwP8T/6224/jYGULI4fjYfTl8jHpowaSHBoT8EUPI6W0i5JAemjByQVsY+RGGkZviW2HkN46Ezemu+P+DTlZ7+hiD2zb46jnBEAumiz46A0bslon9IiE4C6Zaq6tl/N74rQa/t6495/dWtv9vFg+/9Sgh+SHxHMl3v0AXR5vRK3wIY0dao+MvQbEDoGpTV0Sxh1DsrEKxs891CAfy452Y2FlECHZrV0SwxYRg9yg9C6MYSn26EyLY5SyVeyV8RpM7IbDgrSFaWQ0xjzqb5zzJeMlXgekEXqIP8hJ9AK16+AUKLm7OkJ6uG+jieKCkeQ6LvlnSuI1FNUESd8V2ZDx0Uwuv5c/HM5D5zFbGyzZPZbVFX5BOW5SRPlt8bRoGShtfxLXF2isaQ0C1XCOJ9z3vMRjlFZwBYoYLaARVeQPTUurwrAq3Sxo2rNNqh21cVfkhqln8/duRqnIPU1WiRkk3gSB7OBDZ+H7ayjNhfLhbKKMI8tsPIWd/2Hy+qDUb6fsJ3Q4Q/IrrkF8Q8pFj28PciKhnI2KkxbT35FKcu90IZ4v41LGSGPFCLhN957qYbpOQB2pX0n0hFdqVR2nBGPMH9C8kxByJUpWtrZjA28RwJnDomTAmcD4PL6Ry5jJfZ/Z1a1ZZqsH0n/qtJaib3XQDUsig0Y4JARMOoU/K91kWc4zyWWjMYxX4+ukSwe7f2PL4Pj3MJAE+GehXzFT34WJA9y0tQd2upZ+bNVS9/AvogIIWdm3lQdQPjUA5yenIFwNrrSG7oTOQipJSmj9/Tm8NLzj6L/QDulgShXOU7wqkcvrRADIUOjnSYf8mCe1PkmxD45O24ZBZIDl+GPnBcUwgmXboUvsbiiUzIV+tqTDwzjO6nDkBgzL76/SyBKMEraI/BtAVyvy71euqGNFdVUFOaKtFjoECJ9rAQDNPIAaaJzIM1GAxMJAbqs4UQzowQwVGuMh+M6nAbO3NuMgthpg9kwrMpdzQ28L9pdH3F9JX8HRuI7LCAX6TKUctNZ3UU5s5r7KTWGW2TsSzoBPSXyt078FVx0P61dZiXM9OLF5dp1bUxl4dRm2mdLoMtXGWMcpi4S9IlLv6EC6fHlu/3sO7fIkE1gnXwIBOAxGKvsoOfBOms014x8GwTTjyINL/fI84PN/D7wJPl4uJ/j9fT/Qf0R3ZZxkfkD7oRjHnU4P+PxRG/3+PZLaJjesulcfSHbM6tbZPAP0H2Lo73bGvtX2iWVzwMSP/0vjNITN0/04e3FBbQ/aJWqg8vSjd8RuZJsRhBxAFYid1eexijEB2k3IO8wZ6mr83bF1+i/ljnJX2BYtrDp+W5Fr8skH/X2H03ySa3QrLo91GMezXk63DJe/j5o4xm1qCJnt5otngrXXYT+Rgj0EOStMdLWLO/MZgsO1tmTv5IsrteOUE98BwyvXsXsCOv7a0il2F9B/hO/tXBt97XHKLklDTUTAYDG0+BRK1/thRIPTFnECyWISVEUmif+TvsJ3byYzJCXHc66yMii8nvHyAUY/u5+lXx1PXVdMs7QnNUnQlzFL3YIgEh8YQppySV3A3whWEydzyNkQaeeRucgK9mfX77+QWTow19ZVNnBivpfA5PSLNdsPRqHKU6WZr4j+Ur42IZzQLn5wNBgWyv+ZbQvSpNUF9dVOLEUjHxQ28OkVtjA15OiBFxcBkZkqq73HaF3yTq45Nl9nUr8eGb+oPz4Zt6u8w0jYIswARiWnyydCydOjIcE2qWz4vBWJSTY5R9UdIIYc+UIGo+0lcSC7BKDo5nSJZxJcnd2HI398I6SG4E9J7hMLeWt+Jvswmu2l32CabGh3aZK3xnY3iarCNpt24LxjULTImI422HTqhOjcYlOp9gVOqt+i6jBP/YRVF/++noXLGRkatYjYQtYqN5tSq5lQb1Go0+rdbd9ouoVbIL2+wtckvPxNhplGf2kz8MlCi1xvZ2Rf5xQiiTK/wdO5hDHaL9nNdX/DoemOU7XeyAMm+nyPp8gvt7lPhG7yD2nd9693dwKnXx+tNu9saazPtbrryBVAswrDQoLPnHx1oxYOWUGTfjy8i0vmPM5z7PrrGPl+L/Gc4ArwFUExNnk5LnPJ26PJL5W0jpKBaW96ix3lkFTTnYTbgUO3Bl6393SW1zxMVDapqGdPPtD4UhuC9+/ilhkiTnKbbJB/aQQxEDHoOAtFLmjES/saJ3oukiGq2id6xEfQUJXoP2uhJEOetRGeFnJUYy2wlNpXE91Sn7QY/4ZKPlbRMtcH/rrjqkhaQdqhQyxxfvIWXrt5msteog8raXvFT6rdlfAIU69XtBIv2bDPAfUwZZ3HmNZvUMTqQzC7TWZxJzUyu1Z1sdDSuT8CD29vkoP5VyptfUNcGB3WN0fzUOn7+Qn25tO0FPKWeLjX6/4QV+j8b961H/8Bbpy9VJ60r1dVJL5zW2++uV1BqLq2wwKjwTA3izny+B3Ti5Icdp+4s4S24a9qYsntK9THdXIPWh2PAwaDThiuuFjgBvnxNsHxxfPmu3QrIxGXvFYpsDvBlj9B949ewvjGxXH0GgFgTtxIWJP9N7fAW+oqkgFDhimtAKsTdV+MT+RfW/cZFwF8OmPy+EpKjOI57eh8PwBXCcGMx1Li1PvISjUAaVFQjQ/x4G5jOEWnGdKsjwzAdq6X0XHrOQhoCDMup9FzAUrn794YMNrCZpxZfRhd5pJjrIg2r5ucU/zjhwUg+ptd2XDKmWTtwTNdfOiaUMeIhG88WXHZUYwTzqA5HtDEqNLOXn2XXcKuoTE5YyVK5wo7WeGpR0eXwVIfi1niqaDuN7cUIPraXD14ytkkHcWwjIy6hSLheAyP+43oVWMwj69jWyIAinTrDKdQWlt7N07knDoSt2erCy1GclCKd4him6AOt6dUrhZfb/WcLzfTqccFEr1BXjD2oZj1wFF4OA35TaOoBacqs8dCQ1tISNoSGgssN4dnC1kM409J6ZVcVXG5l+xW2XtldzXxnrjjG8ZNpHM8VXG4ujhZcMg4PoAtt7sWwcfQruMz2+byg9fZ58SKBWDcLB7GPtl0CYq9tQxA7FLS03j5/Rf1fEBsG4HLh4TBmFEUvPh5tH+DtRpfS5yqCN3dEuHHmXWzSW0QQt8vFLar6XaNO+bx8QUl4rpZtq8cjcFv9haVyL241w892/cN4cqyDelv+5dZhWb4xffrHOCR9tZWmQQwSP4W4c8phymlu4Ye3luxsgx+ctxOnZn3LJVPjhKqrWiyX7r4kvvtezAztvNdbLMbOqw5hyudPMUy5kVITWCo3fmfYUqetu8xSr1nXeql37WA197CaHdddDsqy15mgbA9B2ZFmPN0ZJIoj/mgTf3TFtUzkFGciUJyrOcVJ30RFFBuQpIv8PbzuwV/fsims87lrL9P54NrWnb/QwjeMcorr2fm1vE65DsRBtvID115uSP9eayARWLDEZswleTmfYuc2/wdwOvjz5cDpkbWXA6f7m5mahsS2YTtaKO4xjaPfEWAk+u1oCYbJ9bdVmlW5bT0tlDB+VKc85BUoLGVKPgareyNftyeazkM5H6YDUSyo3IMPoNdD9vGxccYpqNdxfZWX43jYBIwmp74CefAwGIS3DhdJWMtoX5r1Lp4zY0d70NTqXIsKEPW5dXTEHw/P8COxRajljHOuw8M69wamRI1OTy4jRwe5ySOfVEev5cJ2LfoD46kr0dcHw5YGYjAQklSgglBzZxQ7+yDRlfWBKXjYcoydQt/1Sw+4rJbw0LXFBS9OTQs5+peRo//+xtkF6Y6LovcIin9KusUFkkoAD2YGXhH8J+aM0v4SaYqR80fin6A+ivxXTgCSRChVufGuslkSdsgnWdDDvZ5Bd6P/ik1ulmQJLXfzm/hseuSldEurtyQu3VEi+gcFeQQxuv6SApJS1KcKvCQ1x4ZnhbMbcEJF//sUWWyfOnA1Lpx1Mm9yFlsgZOkeamLIdnJrC/pYXCUJsZKScG0TYs+MFLwnt4kvKbaTRFEnXrzHHHGiuRFxM3MnrFb6YnQkQFoZSt897GmElF2MIJWS/+jjuuBUpP64iu2VbnyvZNix2ymr2T6pVhLeh2Zr3lFf4+VWmcqdUqP1cjUfTVyoPs3LzA8rc3gVL6M9x+IEuR2/eMRh+1FDWUzbV3PL292oHRR2egZdL+Z8RUZKi/eE4FEeIPWku5a0k4f4ZaW2MBXl3YY+d0LHuBkjTPpJdAWHBVZuTHfsmTHIrJ9E9aTvEvWkFOjfEUo7ts75nmknoQGoOr0ED+nawlSUWhx21TuW4q42pctH3dlH0UXa7dguLkAnXthMgz1yI+kKca/ZpORKNXkVIhYX3p3apL3O5TRqXJJra95HT9/pzaSkgS91xC/5T2R8gF/TDhh2+TShDtYI20xyj69jYfBI6eSx20oat8FeVQtW43c8CKQeexyqsABYE/HLSaIvlyEA2l/ia0eQnWCaJxitdhaS6kd5huJCvcBvdrqlmWSfgVJgll0yCUAuu0dghhNJfQk+q61EP9pARvxoLDnag5d4YpfeX82GHqdtv4iHS8u1l8jhNja9ngfgzr7I26xNFZd/y8j1MxfZVVZsP8R2rseY9RkPA7h3qieKkJYSdMJWZvfRnpLkXdznVumTiAzMa6TnLoNNspk2yY46nYHJz9wjyVsIYbnk8265GciSErviKAXFl/G8uxL7EUvlHr2Aqwyr5MS4mGPwOKzLngiU5sUfGcRfEYJ45D3P/MhAfh9bWjxTj0NP1N7nDcU58ZO/ueRZ9kQ3mk1hYaC5m3+8dDOeUj/hrVV75ANoY4U241wAXmw9ldiL53EmTmrxwcv0csvKNnvpuVwvI9k+9QYj53Rk9In5b7VFpMqRDSUihUee8ymeTB4jVjyKG8K+WsHyEvW8EnUt5shF8DZG7XKCDp/GkxhdoEbKj0FXAsuCwWssqJ2KcGcftliqMfSGRxypQlaShZ6HqSm704UTMBc2HFU/dedPdEo3V9NNMvcG+vem+A+OWjFnDzttanMHFlgsweAqlNs9cova9SdG7BYcYKh59TmKhSiu/C4tjeKtqgIv4SO7W3IDRnhL8gQm2JPSAyvaCRYWLj95x+o4Pb4o+kfjxdxHYAEP/sAmupOUXJThdgvFNYfIf2fQD3ybZfxGW2yLxXxpGt7DjFsoEWamB12Z1h2mrOaLkD+9fPa+QP9bPI7+dtFrJ6X7LDtjEagBteZHmo0Fe1Cnt4SFmuOhlXtR52kY1Gfmv8P7e7u5v++G+qusMPc386b/1Nep8O2af9H3WLTu7GIEFRPpWagOWsG1M4NaCF/GGPCZqG7mfdgl+nqyt3yJ62hQmR2Yy52jaHoUkIAP8SoweJ20CgeDeOAxHB2sgzoCOLeUfG1W8JLzFt4gkJT2yMNkH7e14zGp0It9hxUPu0ogCFSj0Vc+T6d2rCQTYOj8Wn6TvaWdwaDVQnedcon3QqTo2wMoXx2Kp5wCQx5812L5OYuDtRRYbIA0nqgBkIYBSOLIHQTS9Dxsh/obG3rG1aYgWQshb1WWft3FfRWSvBXne5z6OextRJA4bhvMi53r5ikuCSy+qzClShK/4Te41J/HSYkjjEpHoYf8+zSe6HoJ7y0/zXiUZ1EUbMDQPHFrbUSftyF2dRacbOcMzBbUB1fgxi1hsX07QzF4SUvsDNwrsEgoBfvbrTtJV7pq9fmjol3nYRKPpeSrL1HVU+p137WQChq/gux5Kr93+qqVBLC+6/jNWA0050GdbRXSUtY7iZ/+6TqcmeCqSHbeQM1egWfmSyWK3uGLIovG+Vo2nmh++1rm05I3L4kFh702gi83v55wln2sC2P24HF32jrLV7CtMxPaqnPZn7gy41+0Peqwm7d/z47hJ1Fc2afw1rdp3+pbww9bIyPLI9djv9wrQgNVej68n4mHSiTOfP9a6kopC8alMLCTFAZ0dFaGfjm4KRzcsosRVCkOLL8JyRRHwF/WwjwypnG//gUrW4Lm6QuWwpaw4Jl0SVzwdJDdo4adY/eQWAtOsTmLNS5uvxGPFhnzFh2BbBbsRTHnlgjmPTGNo1pJkn/HuO78oCTG+nXsksQRxyTkv/9GV0LUwSeeOIXHP7P0CDtXWNF2pMLKpqwHMTQ9uRYBooIrcV78losh+eT5Y6Xg6qVux8npP9A3w+7DThfq0SdPGXB0H4/GneavE2Urv8cROyq+dgUdcWOD1iaHxftlpC6UDvXSV4GhwHvpfo7KK7ogpjZ8i/u+WIsBPgWGUJVSR4APsL4A3mjXt5j1/fd8Y7BVjiC3B/WDB7nQe+CUtylG9DWSMexG8bXl9NAZWEl8ULus6gxyhSR+XCh6P9UnPB1G528fZHd/0DLA9MO0oy9lLO2cOq2mxXQ+qAyWRtCV1V/Tc1j8lq/+HR6/hWIH3fiNKZqOpH0Xij9nmh+1OQR3xsbGFdDamc4vU1wJfb+pPx/FqSulGwr5kOLoPokZD0neIXecQLzk+VkN2dMAcXzxXUuQ1Z5zlMUD41Wul1WncLKyQSjJWzpXsIC0dp/qzG6ZU7RemF3G67sD8/S4GDbNae4XmxdkMY15iQN55r1/cfp030XdeiCfBOmo67/ZlOzV7rhoWl9vw19E35Oh+VF6TvydbfhRVtzww4/THhrQPjRHLHpLkA7BWdbF3QSLUIpwcxX0bmFGgnrlv3S0Ek0cwqfEMluvOh62h15DT/8OF3T5AG077BgMxUlJUr3LSVOQiFNdT4GlrZVvMMoCkjoUA3Dd942+GvK09qYLcyKZiprdoiMXKuyaASQsBUBWChGVxIneD+m4+pDsGtqmGHrbuRZXrubPMC5lEb8ZhjXJmuLtAqy6Kk0NjSX1bq1LAB6gssEplNJyOh2lLvG+2mxgMHBFxddSqFi9+u7yFoqonqR+8A176kdxOTp/QyMGgjgz21jSBN0uW/QVX9cCK2MIVwXJDHNSfeRfut1qFtNjDFTbYRZGTyKdIm7XUl98BdtDAxa/jvVOqfu/4fxhHLFhM2PFlamxg6MzYgYnZSaG8MlIQQJZZHBSxjl4V8t5YTUDugPiVwfRV4WM2hn9fhrE1YLW+aK+rqLvs0aGzRP14+6J2LMkFzA8yYXuQP926syvOCtLcScEKuEBQuXw2BOn/6pYf9lFDHkSrnMlHkGKRDmCMLq3vIG1Plrfo6PVKw/BPBYi3DjZbaZLNXbOMA5bHD1jDA16IWwN2qjyKeQU1Mhv2C4dre48aNqlo5FTmHGVrArHwjdqdhPt0wJoP1XDffoa26cgv2p3NYTwje8zSKjWL5H6FnBE+o3u6DYSH6pPeRtiRP9sKMd200zYqlojQqejQFwQ2UTXTfaCXdjQeOn5W6B/amv6V4FTbtC/1y0G/XufJmkM0r2dLvkIqix3f8X4gkQEoZQMD5Cix3ai6QWoUHuBTzajlZwezVG0qY0h//8v9N2+C5mIrXw4vgVROok1yNgZPNHVn50vM+HhcQB+Wk8+tFb4Nv2AgW8bLZfg29KjbeFbx790fCse+H/Dt5Utl+DbMDqE+Lb3Mr4vt7SE8C1u84+W6fHrfmph99y3ia9rPuf1FzaF4evxy3R8/UITM32HoccJX4XQo0T71/pdoBV6zP/SQI+RVssfQmnnGW586giB8NEQbnz4j7Tyzf+GGHM5Ysz6SkeMc780I8aGL9pAjHq8768+4/PXJaoVXnQua4UXe6knP2d4sRfhxZRwvJg1n+HF9V9yvNg5HC9GAV6Muxw+nPCZjg93Iz68oOPDcP7qFuiStqKBiYbqOOiN9mZjCDjCgIvHR9z4KR9fuwtULUmHEdX5GR+fVoOgY5IMWAuk4YYBoXGogl1k/pt+kbl/GYkKcj0/gt1LEQgzYYA9ItqTkTxnNhnwj3t7CXOq2QnLof2ZgJJ3NdHEj3XX+/sjKQYijf3w3We6sQXFDNSvjPuMrYaNVuPuhrDVOPMqW41BX/DVuLohbDXawWp0mbjwcuvx2yf6ehzBe/WiDeTaHXvfh7Ek8w6GsSQXz0DJ7EYGjEUwDu3L+ja2nvZ5aOu1NNLWu/NVLvPS7oOFTvtcj7E1IuKP7byvCXcPqTlAO+99SJUh5BJf8kfamYAnZmFhBSCicjkgvQKG9ArEewv0rUc6n9fuaiTA6qValun7r93n5v038zN9/4m5LwZN695J7fsxX21bRKvdV/TJJVzJtE/MXMmt4bsvQmbrfc/nfL3FP7D7jnykr/ZO3H2NJn4WN1o99FIbfiGs5zM+4j1f3ApOO3zSGk7zPjbD6Q9NYf0elcv6/eZnvN9vNZn6nZQZc7k+32b0eTyeW8GdF8ZEYERa7M9d2PlU83broq4E3hVHxg7emQYg43Clj9lbHMVvbAjnPzIPYUpz2BDmzWNDqPiUD8HT/L9P/dMf6sPohvLmHc0cuXnhi9o96AL2Ij41XjSJsD+fDOGVy9kT5eZLLYpDP77Uotj7Y1LDUkhitCx6myMzeqDWFgZ2GwxM/ftHPAgiXjUMBWHfv7bvv5ge66BOynrkRZK45ZHWhFkePYEpMaPdyZtNlsdtH3KR/1wkw6c20beLJncwwH4DszwOMiyPs3TLIzM6zrKGbIVme+P+xtmFhr3R7fhN9H5G9sY0Zm9MMeyNV2nPRPIDgmb74dHL2w+lQd3Qfmhh9kNmLDwFPGiQXfbUi11ciJcbVOJ1BzkY1VfKbmR2wlpuJ4z7gOyEzr2X2Alv2fs/2AkbfzfshHW//xc74dbfw+yEhZvIOjhL6bti03+wE772flt2wugPDDvh87+TnfBv77dlJ9z/fshOGKJvg3hZX1jZH/Sy2uRL7IU/kj6STjS6hR1kLPzE0Gt7TwiSMoMfZyB7oUPQTzOu4rbCwdDevQ5P9/Bz5WQn3OlRot2Oxhl3s3OMY5ih0OXYKi6o0s8x7mLnGA9GjQrEdIfy+jkGl1wFbUDt6YVuxzm0EkKPj6D3A1kJn2QHGcbvCRmWc110gjkKKV85aU+srj2o9TzAriPxKL4Kdrm49eJuo1oW2aOzq9HS6HGgNS+gUGWQAj0gE82yDw43OOb90zA4QmntiWaTvgJ6ikf6oKPGuYd7KZx/rYYX97KBdMT3uAMGB7k7x1ydH2N2SLI0ucfXsU/iYRY0QSaqd3/Av8xCSqMJEm+QbWV9XBZuffwBrY/2JYaa7JBufdxx8b9bHy8C4GjfhVkfSSEJKERNov2FtACtjLAbtedZuJ/Nu7i3EEZfbuUr1C/c+LhoFxkfx8KSvE7RYXdhnGp0nZqANsQ6PLlwioyPLj3gj4/7622knffortDO20NGN4UCXW9xynVuuVlJuGMjc53Cq5WVBDtL5X5BQ3LhtR5kOWR0qKaDeuEf3K4nUchk3VU34z2TXS9O+ztUlx+zJzoxFOoWt9wCNQv+0aZF8C69JoxNif1kJ91Qk+iST3rkeq1/8DLdyGi7Gyf+EdaNPmwzm+Rt/RLFBx8A0pSYTwJ43E5+7MBKkbcz0JjZXBPD9FqK9fQOdGjEQ6qQ6nmQUquTKPUVXQ6ufIyHD9L8wYzuLrlJCnzfS2CeuXFZPFJLN4QuCtACwlPmV07vESHzU/Txnn2NROAaGPDVK9jgTJv6EsyHXITdGU8KddgGI0kaOCkFhqBFBTi65/+B9iU8fh0Y8g/gXdWnIAM6IPrcZNVoQn02fR17QcSR+rEA5zoQu303siYtZLfSS6hvvNsSLGmc6qNUSeMc9NTxBoWMSc7Awy3IRFM7dawlT8AXnwTpGpj/mYlAYmZYgSzGJOJ1nR5HfsbtEouSA/sQMgeNjpuxPfCsgME34+hGT/kYjgfDD8GH4rFK5q8wlifnkF2i4HCUFHjMHqcueBf7O6VPkum+qgdgc98OZe9lZb1FcerfsJjj98wDkD0KZ2i3umIxZGUX4wrLO0w0Bdbz2u3YzDLEahQ0gU3j/tk0sz2gqZpSFgZqnT43MGWf7AIRLY7p3yctJjPbD6zGMUjVzNX79wBVlbzH4xDAY9TjCJDegZaMBNj327cxstq+NOcfyLek7EYz20/YnLc4DvpZtNCon4T1e6hfY325kJpIBFTbg1+1aVNz6hgOtiFzs12dwVpJwlZM8N66vccu296TB8Pau/5/ay/msu3dVh3W3pZ3/qf21rx7ufaG7Qxrz9t2e9DSQJp5tMbGUeMUOVEd/y631mEM/jJ2Z0aMt0EQfWi3Fxd8x918krxqhISmZXfgWRtZrdMDU0rjQvD3OMb7vt7pvdg3My7rZeGvmR2yXo7AuM606QdsnMVCen//DjMr0v2WWHgwFM7ImErP/eB5quh7x8LfJUH6GdGPgRKoMf+ntDOHfACNqdpbONISm9txIjNLYncB81uBeyEhqFdfeBtQxg4ePxGGDfMysIjxJ9hcpiIFEhyzqHuDZrFdUwI4Z8jfsfmboTI0LfqvxUuBPtDjVVM3/kLod0iXWURDbOoTb/GyqF/SpgUpOnxf0f84Rox+WfhbxmiWTmfpiYA8KD2EpSeJ/tvpCdtOZm2XvszbjtDbfhfbjuemc+r/l1But5+X27WIl3sOyx1vMZV7w1zuO72cG8sV63a0wJDrXiYM8cYiDGSh8xUwNR1epjkfgq/zoUBnnPdAguVlJt++zO4vGtL7ZbyfdREFbG98iaok0zu1mmUeY5nXscyNLLOHnzK7s8yVLPNWlhnPMj9kmT+w6rEscz5mhq+5Fm22r3mPj0V4j0J4H4iAm0rXAaoz3iZXF9pI7b2z7FFRc65HuLwHGpRViaJ/QWupACtji8z3t4Fcw+Uz3A4S0aS5bzHBzS2XZA2F9cTbQbLmCLCKS2hPoLRmfaQQ71WY4FGSqMz7RplF7Nauyey9pIB08nKSbszs/RZt+JT8NP+JmR1djr5vV+J9KPeVAIuXBDjz6UriuOwWvj/jaHMiFu0o57uUPjnoJe3G2ZFwdkannNASTPeN6J/xvcF8gdxyMfbOR7cL8neT3iDnAu0pyPs5kYJcwne4XUv+/9g79/ioinuBnyQbWCCw4SVRQFcJNiiBhJeBENjNQzYQIEKA8ExCskmWbJJl92we8gpmo1nXQEBErdZGsb2o1NL6ABExGEKCrYqoLV5aia/2bCMCUjGKkDu/eZydHfZY/7j/3M/n0q6Z8505vzPnN7+ZM+/5VxbpaN+5k1QtBlrGtcvbYYLK57A+tntH8HwaJwhW64pQIUTVNHusHr1DFO66exslQPdezfJvl2b5911w+bfzJ8s/bA8xtPyzQ/kH2cHbTsq/h0kzb85JWg/dGmLPSYdv+AjwR3cb8Wg+3XUyGX1C+5wkiREnNvrW8Y2+rve4Rh+kUJwvvrMVt/ecvvhD2GXw4hOTUcoZoSw7r7ywg5RldlKWxZCyLNB+29Astgn1yKq/bVbbhGvRU/HxGKT/dR4Nv40Lf15pZ+H9LlJFVMY00/4kR+AsNBL28WbWT7ukN8T+qV9ZcMrR2T8ofyo9OwNZrx96kVH1VyO23E5P6TyrnGhmOdAI7x2H3tDSFsh/RbEJav6TY5PMR/rT03FNOCte2RHUh5KJKhCPNau2XX9VJ6P6UZoRfaMSLLg36YdtpC8QupPk/srKHfRSWU/eS55iNhz5CzZyOJAFZmx7jypT8CSSIrpAHLajM6EcktLLxo0EP//NVDWiPX+1Q8ueTx24xtvzS9t/Vv3gSU15qYeC5BVu18ofNSBpigUfUQ+lHSkv03YEEi0KlZdTIreMUZPshu0sySyQZNlIcE0bnddWFJvL5kw1Rf7mDSjjIOFKIckcKFn0JHppzUK6HTOjpPv7NhppqJr40mIMr6Lv8n0KPsKLHb2Oc6wdKilH3s9qyoKtY1pJ51YSsZjLsMqg/o8oiu3Qsh9HJzboIapJqDwehuXM9b0cnYv/PhSdjc07I8wy/bhrIZyX3BCFmj5HJCPdvIBOqX9vrtczJBfrADWnla7teBAUN5W+gBP7mGjc2oaw2RJ7dIfOT4bzUtFju+hZF+hrAIc9RsfgQx93RUPX7QLvy9GwUPTY0/du3hUNB5Qe2+O/zRMNB3+EpSLPY9izdosnmhyae74VFULDEal4MnoYDl6Agkfjjlf8aO+7c5t20cB/SY1L7d0VfVoiFovP+SkFi3Uga74NH2MeRP2DrrF1I3bYcHSDkRTjXjyTuSyuMYscUm1ULjWRrgaj4VVutjOqz2d6UXJNxYdjTF3qkqRGOFIKn2uNv2h4XvLS7SQTRsPNMQE9otw43BdHelZgzSd0KOHCGZIS1Ua/huendniGd7G9zaKQJBwDXghKiuH4SHjPInrWfb7/zatk/1zvu6CQ5pAKGczNT2nSTYOOFf9Fcl8WtMfR26KHD+liBzNhq3iQmvD174LVA2ZxGsdlBa4gpyxyYp3Aaww5SCUpS5quew0YAoUd9W5in+mw68NA27/94vkTKMFvaCF2UuG5AffDwgHJhgNTF51ARpg6qtiQdCEy/QS0jdcmFHtTp6HPUya6bJw7xdTonNr+/eZUY+Ip0H9U4qm6g+Q490feQjl68WuQo1O9qJGK9VgNvUXHvXgXgJJXcSpboHrsm4FrMUq371pvIM817RtOdoPeJCkXm2DWZAbdlhrr3g6byqm213QFiS4joqOI6PYNnOhm37XekDfm4BneUMrEk7vffQXf/Xv+7kU+2jeW6UtSrE3sokM7PuFXrs8f/h96e5t/onz+0adVPr+1P6h8bvP+rPJ+n6a8tceD5Ll+nrxVPtoeH4yloGr+f7eRSQZ6aIvHc1Jw+S7eP0ozPs4fg+LzeePPis+fH9SSN+SzIHkP/zx5GzXl7fwuSF7az5M3XlPeN9OD6qOXHvhZ8v7m1XzfDUHy9oSWtwTO71piziGndlGxw5QGL1e7hd5e9AUfFmbYtok0Pa69gpse6T5U/rahJmmvwTMSOrV9m6Dr7UQ5FDdQJbr2AK0cwSbl7sL6FH07KqDmF35huP8DMlnnq2N0gm+qb2aL8tQr13rn276AU/qyIsb2IL8LmfWe2Dro3OnuB98RWgM/r3xwP95EQkHvA51Rq9vYvLmpC9DjFc8DpNfPvQZFd+IruHq+9xiOdR1S1XiItPdjsyHjz9D0udFSeMJiO4FPB3y5Pz4dEH3Dk+CbfFySUHxppC7Mrd93G46Nv4bUcxPP+Cv4/bvrUm49hkvnqTCLZ2RvYD5fSlYZmU+pVw48QGqKqdzkcNcDtAQxe48Vmb2Sb+Df21DxOv1Tw3bYzbOoI0IiC1r9u/n5qKjiAlPt1eOAc5BNnL6fiiKnAacjOykyd9DulpR722BVTF0b6B2l27xw3CH+a4u3hxwAbDmqhFu+Ow3zWfumN6XqM6Z3ZhhSj6Y3ZfZmwPmaOeF4mGpd8l0GD7j39jF47kF/k6t1Bs8a2HXlh3DD/XMx0Rs8JRBER4ImV0cZPGk4CBz/Wx1t8BTiKzj+t3qYwTMfX/U1NEzHoWNI9MzeU2bvCTj+F31FHzWPex8fAJx4KsPbaa7v6um+8z+f/2ueftLg8YbxBwB/aW7SDWnvqfa+NX3KowZPPnT0NuWjxtafDfXTcK/vZ8ngMZd4hGOP0ZxHIvGIwB46ziOGeOiwR7cU8OiVsEck9jjFefyDePTBHq9xHu8Qj77Yo4XzeJl46LHHA5zHE8SjH/JwORm8n8D+AFcTKLsRGAAgi4IiBKIAJFOwGIGBAO6gIBWBQQBupCARAQMA1CbvSp7ygGwEA52DN77eh/MRqkMOTziKWpAvoe88mHa6d4z/dhQA2ZI8NK1JFw4LlGvIybTQAwWrfw8hKd0fkfE+fxhMtjqEzza8DAceHsZ9yQfMhyFDdP/ejNcP+M9gLwjV/aT5ED7EsBMjOMWw22s+DH0F3VvNh7FXlZovxf7lhzxQnnbQLuamyNg/kDLjID5V0h2NPnDL7+P6l4sshXXiEZWmVtItPYYdOPoQOXD0hDxYPUVSbT81Re7Yjx+BCprup5uhPLZs/SohjLSXUbNq9Wla5pUrytf1XLH8MV5g4b6QjmoTU8z111Dx/AZG1i5arpgP9+LlAZt6cFM3uh43yVA7CYUONzTA/PTA2YNKwX0wYAGH5A7c/CYpqqAbagiOXvu1LemxJjyMkV/kwwe7xtX/0CuPgsWX5DUtYZ3Jw+PgTsN8fLZnHLr7i99L+Gj5t3DJp56jbPF5wo1sd6oYXdAprDIMtx/uD00X1DhC3xEjtKjwepK6I6Qm6YFz3NTzYGHg0PfyJGi8oIZiNCoooFLLfI99vv42zyTcnsGjmiY4oGq1Dq8zp50GMsw/kFHr0nvaUt8dNhbGbkn/Q6TUX4eiNOw4WXLTpBuAV1qRED7PcSm7BVfbHZZxJ8mRUnSBSa/yxy10DsRyaACOazN4TurwyofuM/jcDSi1sd79dVBcW7uyfJt6snzuC+on7sIW0nVTjlrKq0+fwOtFMrl1C6atZN1CEtd/Cf0a3h9AI/CaC8gGAN6TONb0HdNR26QTR5atb8PxDd+i9se1yRaIJ+6PW7k5uD8u7br+uCRYAZmEms8zcX/cjK18fxxue8GZJhbvSaI1olKizlS6BIekOSBQNTRzkDGBXvODNU2UXArDstvCw7hzuSEhUdXDEwFRSE82GhoG8N71hyMa8QHMDUmk0bTEimKaUEfn9xwIdGzCp1hBmiBzDWClUKb3uDJtKznOEy9NMpPZ98/vI5sBe4tis1Tr7Y1+PYF2eJpIFvDp9LCeAx/4iV4oV+zvwuv18PnOm6i92MKxvchR0Cd6lrYfg47JjcvyztTTeoVqR6hk+vVmZknuC2BN/levBuofKO3R26R7jUpNHV59N8LniQWtcGuPPLvC+Ec1Rb7yArxThw6ms0n01eRYkxB/vKDqrY3EfoZjWy+CmQbIhlj8laEbmR39GdvRlR9FO3KAKh3IjmRsR9+gl+luQWl1XyHZfXYrAlwqpW7Gs/AsWCFk3j6KJGtrNrhIQo9Yi0TNCb5TvxlPkUrH+eUokmGC4szYcGbzeiwMzFWV8zFMM82JNfkPwBz+ZlRNut6M5xAzhi9Z4lW2j/pPh+tHw+FAOH9wAXEGqFfI6a/+T8iR0uwAemLJ8BWbArPJXr9XnWhRxyZa/PrKf8iju5Gt+e9BoZqVDYH74ZwJfH/elRBpI3NpsxTuh9U3zRB1/8wfuX6OlM8LYL7pxiCVP7IRD/F+UIBLa5PySrB3FfFel4+905Xdwd59N7C1et63YLvopSgHhlQcK1D8z19Rx6FShuXD+b3BEiM3BkwAhHiPQ7TgKyWDIRi2n/iBPiJI/N1U/LzAOp2tXz1G+7bHwyejFJfeSsZGtooAKhJDoV/U4bPHjq+/GrnlZuh8ckCzKEYZeC8U8VB6lVq2HgNJbdADij4jbWqn9cs4l8Ka1Tq6GSfp4kdf9FkbxAmAw5Q7CIthTBerjCCIjRGhb4aiIygucKdOuXAvVgosf4F58vVX+xgaOlCe4vsnoJBuaK29oXsSnW+eXEP7+WUy4zX6UBibjaK8V6uu/12KfMnCapjoh8INQyUHzIt9gYa5QZ4Mhd5sS1h7dxc3PnGmmpUbb+MlIldwde0KajpEIJEHschxp/FymW9oR2124mVcX0SlEp5RqFRvIA2iXN/M2AxoMWXF4kGdBFSNJVNxP6qhhW87XeNmwrXMAc3Kymoy3gGNa506jmFSPqim6xECb0XXX7P53dV8eQjjpfBqankYUR1cHu65JuY5C+Q5iEsWznOf1UJ5iN5imBAsaP7UYRTK/ysk600oJJSUWnIyRjZ688RTMLhRhhIZawd/3JRV90KAVbG5+OiiPfTt8f4yxL7vRB/WgyCLrnLuNpB0T6sienHBQR3wEbimdFWT2imMA8krs2AuZVs3HfdThtLwE5iG/qk0VxENfY7a3+PakHZQHLZ0Bc8vygqzQ8c7RHD6KliyQxa89ip73OhFF+Glsig3QbdaTeIZWGlbR3ezaqQ7AzXjA83xflsb2EiQElmDPx7R/vFXhf63QNfK1hrSPQ852FS/MXZU2ObpkOvoTF/SlD9cTeekNbR6O2oTYQbKe8pdVXyvFykXveR0HGVkkJ9E6xno432qhvTkNEVmP0sGdr3RWHL3vp/q/6nW6v9ZdF9w/487dP8PHpOBt47Bw5yKrzowbhMP49xhW5J9KQXP0vE7kgPARPDbvCOD1J5eeWLiORjYSSFPifEqK1e3kXW2NXqmdEhvb0f3AbzuOTL8JXwcV4fyvetab+I5X5ISjTSQ1RTZsVKSXnt/OD728N2VsLIYFpXNa8GdOznFkMeTEluVU+hR3T4U8VJ1vJCMPymdVdzQE4wXNmVcre8JrwqMP+2Wrxt/KmXjT7I6/gQjTjBmoVf+4iblLCoV8Vj8NnUs3kPqSQP30LH6pPqrEaS9Tedcj1zJOsMuoocmnoI9AcjwYdNU/Uo4D16mGRLGmt7AJfw1KD/eqqKqtaPCpRu14JZIdTMkdwV0HudC53F+4jn/RDYuy3T8NxeuqdIBWxOxLyrRwSTeBEbSlPLoCjwlotYFO1Ko51Uy6f53UeZqhgzQBE2wpuGFODg+yV6xukAhm7BNGJURz6K8CDW+4mbSZp+utq8D9kWmESl3ugOJY0b2FRW2GSVgymAkXDn/HFRMa5LhmcOfX4Zap0aJdGuh70riOeW8EycD3kQiWnkaZr/D+K8T21wStjnlhfWoXE1SjrlxjaJzOWj/OHrLNsRxXLr/pJHfd8iB/J5N8nummN9RPn0bvfohAywu6ofKZbywrFqmhQD0AXjfM+xqU6Y4+Wxu4vJ/kAc/v8pO9vKIUfQy2ZyBTTWJCt8SR7I9rE9cT2oMEDrEeD7Ybxxnvwm4nnCDC0+FOZULnWkdFl9GNB5YO66sdpJuUnkZ8j6Si3e3VywMrkXwZQonM1gOkyspvJlCdw20IFvWw2cWGtOwVAbPQ25GnOxj0uYI8kyk9on8kdX+NtiTTFai+/H24u0olPrgIBfVccXLKJlvzcWWfLYyKEwnXrT3VZyq3xg8iU3Z61T1a/A8EYk7t6PCDNuaI4j+kGJNeqqgqEpirtC+QFVB6bIpDtWUp0XilWzo0cMPLSNFyqVKWCJBRzfPUvtV/k5ouEqfAtpBaIRKHwf6B0J1Km0C+gShkSr1Am0gtI9KNwGtJLSvSmWgywnVq7QMaBqh/VRaDDSe0P4qXQt0BKEDVLoGaBihUSpdDLS7AtOBKs0E+hGhg1Q6B+ibhBpUmgL0OUKjVToZ6MOEDlbp7UA3ETpEpSOBlhA6VKUGoPcQOkylkUCTCR2u0h+WIjqW0BtUehGogdARKlWAfl+OaYxKPwf6OaE3qvQs0HcIvUmlHwA9QOhIlXYCfZrQUSo9DNRH6GiV/hGom9CbVfoc0DxCb1HpHqCZhBpV+ijQyYTeqtJdQEcTeptKHwLal9AxKr0f6EU7prEq3Qr0DKFjVboBaLud5FQjVJjOK33KWaEWwyZcxrWx9ltuDrphip1sxQPuOOJeDO5RxI3DRBP3UnDriHsVuHvKsHsFuL8i7pXg7ioLhPmQuAvA3UncJeA+TNzl4N5P3HZwP8u5HyNuGdwPce46zi0T93pwlxK3A9yriLsC3NmcO517bhLHxxN3JbiNnPxhxH0vuPXEXQPuH9dhdzW4LxC3G9xfcO7TxF0F7j+vC8hpXReQ8zJxbwH3XuLeCu4nibsB3M3E/SC4PcS9Ddw1yO0feo3Oe/gOpx/8NZWpZWvDi3AqBxiE0D+Gv3v+04F+LDo/DM/HS4BCPYnMN/rArtYrDB6YIIGMSYcXEPUJo/MGFUMZ2Vnsr2QhZNQhSYqWjsDuUejj8Uc7XiUYdURPrp9B169Bw4fklKbhNy6EOhquixgWdqIQ+eugQocrI+hVjyxGsWhCT6i/Gm7wPEk6FlBVZfinC/AE2HNUDrpduX0dX5E5/ctrsDQ1Sq3tDH9xAQv5o43UPEnIF39Jqjx/sbH6awKelESnvOH136Wk/kPs/8bFav2nlNV/jpDvpgwT4NLYdy62lG0IJW+Eb5xcAbEPRBlHa8QCWD9ow/s/QTM6B/HLyvelYvTPz2fRTwkKjL+OqB7XUUpyvylQfwV7iF5H7CLOpm5O1QAjNXh2XZqNJI8yw8Zuju/F3/dA/Z+fr9u2LlDPvAnX6mGcZJS5/ppuyx24lqu2BhpLr5vCW8rabdfN36WNAlSpOmoL6nxBMVZeJChGXSlp9rYbXu0Li6k/kMg2WNxU3YRSqKsfQ1GKJPPaoUMG1a7mL4T4I8+AfaZ7z3NrNvUoPSPQ+3GDN8/i9NPFzm/4Qk40e79OPDff28U2ZMocp9AmwN+LaT/HRtgpQo/a3FnTv3R+CM3EhlOyHubl/ncJvMOUWNKpfE6ZW0pmyZDpwFz74Ci0D2bGu/vjlhAen2GLYJeWkJaGwdMPL0ZLh432UCvCf5XND1ciisFOUdO1ac6P9T2jqm+wNA08vxqW6Om2WsI6e7tIfveRddYNsGuoct6GjbosW5Jo4oFlw37kaoSVJ0qCo7uRTMHJ9Q+BYfNmsugd8p8/HOqnYKbcUQAwtTgOJd54sv8denX/maD9pYKSBD18Y2lQMowuwV1odH9enByGhnKYMP8cKf9QW/HTXaR5T+cjQmvtH2r5BtvA4P1XFhfT6SW+GXQvxzp+fmwUnsxK2gunS7ilGDAPw1Kf4tuDx8kGkqvfkateNnv5UBpu6sVfbqYjgHjyMVLt6GUwi2M++t6CbSLHoZjANgopOjDMm5hPKucTD1UpCQqCgbfvwfttep4Jo5OdE8/ANtzn8JRblAO674LyJ9WnO5iJGpD3LPIeTff+AMXG1AR4eH1HmPIdStH05JS/PSNJuStcdsvWNjy+6Iv8xzP41LeYugx8FE9MI2zt6NsV04z/PhTzWAY5BweChb2TGfYhTJXehZ+TeGJR9+7iZjq49p3ycBFb45HE2lGWtuLm697sElRXbi+BodFlrZaGc/Km9gvLTkC6NuIZckcv3XGs/cryyBdW4sVlNRXHPr10xzvtV9YcxW00PJsXIpDl/Qy94rmlMFCD13crg61UkWm8ikGRB4qJDcfhadv++dz8+4BQaLJDu1Kp/zLM8r5i6afAkzvbL+We6K7j9peEHUeRf/1nYZZ+JyFIa/uV3Fa/ha7LDXpfmHzelCLh+mAxeWX/7F7e/jn7gxnl2P5yrdyodAJZ1hf1NE19FN8o3Lc4BDZBg+9xvzA6/5qWg8frJXIoMypT49fCm6e826KeymzueIAdT4Q/rIeYtTZlXM1sWo3nBifNb5LbY+h4WPKRGaDdh9cGdjh8Ew6TQW/n+y8jLqQs9W16VNb24AjAiabKKwVQsmwKo1Ga5/XMxGe0+lLSWtQble0oFD4AFXknEO9Y5G324SjWt4aZvdiVNf2SPCAFtiAw3I/7K0layuT7QpIv8Qw+DwwDdcT3WsF1k/Xpdx2inDn9E0MDTCnqfjGwfg92b6XjD7DD5V66/SUMJShvFuIPDJ04vyp2fP2ViC3x9Gn/VJrp0+hdPnIX3uQT9tCj6zX2wStK3GjEQToasZ+ORrSy0Yj9SOXzfVAb8rZn4o2t4FtVf0Un35oJ22jUzZYMDXfCFk9XIuVBgOIwMsPxbm9CGUw6rRvXBtrciX3gOEopXFKca1nvssFj6oPXOjR+AgaCc5P3Ttwz+QZuaXdIIKzDhIthPERQnO5N08G2CNjKG3oNjfABeZMU+TOHFns3DtVldqRH4hvNyKGPoOXEgDwyV+tuXCtCVSaL3tJwAg7DNkdn+RzRWdMvyHcE8kemb7MeZtn2w2/2Lt6foAoCub+k9gmVmVfXEKFmLDSZCZ3ECx279SrMH5dHB4scykQmr492f9GMvhC6hlPuQaiQNz5FNm6DWLx5Zsqrf73vk5FpqDT8w6+EPTTlLN/Uf/8KHykpp4DlZGNFKBfWQP2rx/JdUWyuxZYVmw27rFiO/muIpUk3GDbfrR+E1Js57ni695vM+muFVZGHikBLhd/irawvK7MLoH4t+wze+ZBdjGvI0JCnupdskHB+NTzgvPLP1fBtI4YFXfb7aZc9O8UKnw6wBL6JzWwrizfI2v/EU5B43jTYTRbV7/0rWH0iq/CqWg/Lio1e0KS7knn0n7r69jAykXdYPp0T9xq0yOvBEtI60lPwuHax2WvR4Q3RzF6UgH1AvfO86SkS6NjQIMPnexfrbyq8qvYHZsXGCM+JVvbl0R2yScsflsvjhyHJ6DEOHRKPnwuvoz4Hkj1z+nGD5xP0ziTZDQ1/hO1D3rlK3y/TezaxteHcFqP/rnD+gAILKnXQN1OPbx8Fk+Uuz+lzo6yQk6btkZIvA4YmUBTMhl3H63siUCXSrEdhZ4RD7c7sm62O1yUot6yhG899CqsjXk2PTZjZ3+D5Ao4B/7ppSVhj+pTs+quzEIEM91H3W1B+dUT+5glSPENTaOqQOfgzNnQOtH/X4NZK4hnl8kqS8F+v/BkJX3CFm9/I6so5a3Dub2jdcofBcxgW03dEjqcP9u+7Elh8ducamBTT4f8D2UOA2fawVejJB9VcASaejur8QVYe9j6edRJ5+pdIZu4VfOjTdjroifd4KKQtyWzyiUlYRbfIw8cLths8sK3b8UCcW1YHfVTwGOtDq/FnCevq+wysq3+iP0oO4l4/SEvATah9Jtr7rfywkrUyE1DgP0HgX6zGLS5dIPgmNfifgoL/FoL3oHj6XTDFDp4KyL8cXcmDlc0raA6twx//y17leLouG4rWBn0vhM/wXHb3BZOKlo+heyNmo3thK2c8MITqsgPwK0w1wB9D+gVocWaAJSge0A2qWwQahbGpbEPCODWK2eiG75F1+2FvVu+/vB/5y67SaF4mnT9vQ1vhLqxoFBx8UjoBxcI7/fpqIN0nryKLDp/BQ4L/wcS+78EFkt95RdzPgB//WxUYDygl4wEFQeMBulhk2q9jk46KhfG/mruRSnY20mWZMaiOEwUbCMesIkFg6OUWaMOi1/B+gu49Sz1wU2lXW3dfWj+FMcRLy7XWW8FK44xH2f7gI7GRpfx7NwP9Cdijgu+x9lIWqUAhIEwFfyVg/yMMHCcgTwWvEDBIBc8S8MYuBh4mwK6C+wgYqYL1BLz9MAP5BNSqYCEBcSqYRcBfdzIQT8D9KhhFwFQVDCDgix0MQP5B4GEV+AlIVcFpAi6yxpDSQUCLCl4lYKEKfkPAte0M7CLgdyqoJ2CVCpwEDFBBAQGHtjGQTYBNBbMJiFHBBAI6mhgYTUCVCqIIGKuCKysw+PAhBv5FQL0KPiZgkgo6CfjUx8ABAppV8FsCZqvgkRWwgQayV32bJF0y3PwDtlNy+f///v/f/9l/C9EPVmxCJRSaE3W76iw50TGDf6n/t7GxpV/lVmnnCknySIPqtuoH63dnsvvgnuXot0KQt5L+XUX/rka/NeiXF+LZsGSzAP3WhvAr4txW9Cuhbhv6reP8ytDPzl2X078V6FeJfg70Wy/IdqKfi7plaDBwflX0bzX61VD3vei34WfociP9C4uINqPfFsG/96TnkSVtQ75eVvthVclLz51te/3QuFuKXjMcLbvFuCnd8MKm2m0TH9lRVjvo8Gdp345sX/Tto49n3C/dGd1W/btXo2oaPriUNOGeWvN256Vnd3keX/aPZe9tvZi8ePTz27c+sWjEmM9+WfaLOZ0PLOuoOfbrSS+efX/hv2dtWjLt+Q1jno+at+Hd2SNufv9XXRdHT/vVgXd3LztvvG397z58Kv5B5anJI6sXLpn12/8aI+/+6qfebS+qTg8Jwf8VBh2G1//7Vgod3hsRmldr8DFhofkSDfnlGvF8XIND3I0h+Gvhod8rSUPOPo145mm813INnqDBH9Z4rkfjuY9ryHlOCv1ebg19ZmjI+VzjubdqhK+KCP3clzTkbNSIj1EjXQ5ryInUiM9mjfA3aPD3NfhhjXi+rcELNdLxXQ1erCHnN1p603hfowbfoKHPlRrxOasRnzCNfHS+jyQNDsFnacRnk0Z8hmuEf08jPh0a8X9ag8/VeG6Yhp57NMq9pzXiI2s89xmN93pSQ06RRj5q0wg/UiP+92g8t0lDTpxG+EEa8ss15NRryPlaQz/nNOznI43wOzX4VQ3+Dw0+XsOe12q8r1mD/11D/g4NPdyNfreF4N0a+vxYwx4uazw3SsPO2zTi/4jGc33hodNlH06vG6Uu+FDC94x9TyMpTw7m8TR8/oxgfisLnxLMH6HhjdOD+es6ymcH8xexnnVS8/NkkOWZcGq3VL5xVnD4LyMIbzEH82P0uS3Cey1h7yvEJ5HKbxHiP4jFU5Bfy8LPDOaZNHy+KZiXMP0I4dfT8F2CHvqweAp6fobJF8I3Ufn5gvzPGRfS8R32XEGfTzM9C3KusOcK4b9l4QX5J2i6dAl6u5Gli/BeZ5hdCel1iulZkF/Hwgvp2EXj2SLE08u4oLdiFh9BzmUa/3wh/jnsfQU7uYXpU0j3JPZcgaexdBHkpLP8IuhnNbNDQY6Ul1dSXlmR55ILnHJenpSXmTM/r8jqtJbYXLLVmTM/zV5ZYc0pWGu3Er/QPnmFNQV5xbaKArvtXri0Op0VlXn2ysIC2VZZIblkZ2G5Q3LVugorK4rh0m6tQMFsrsrCSZPRw51ypd0uOZzWgqJpUyS3y261OiQHMITsSI601lZRlFfgdBbU5lnt1nJrhSyVW8sLS51SpcNagW6Ce0WRkstWYi13yLUuqwzugqIi6nI4KwvLC1xl6CEuW02ey1FQXeGQqgtsssNWJDlsDqtUXFgh25FgLgR6Rbs1r6AQXsqVZ6uwydq+6FlFbseknwxQaK90WbVDFFnRa1TWQnyRZiWXw24rtEquCofTViEXw/vD2yDly7UOa95a0LfkKiy1FuUhXlBcDBGsxcpHaioGBVYVOG04xTh1CsyFFBhg5QVl1rwKa7UYNljRbpRQJVYZLmwVJSiU3W3FqY3STiovQ/ZS7oB0rbDbKsqkcndFeYEDXa0NipJLRnaH4lnttMlw5awAmyknyS8+T1rrttllWwVYWqVTKkcC0QMKSWBrFTKP4iKQQbyLkXnLyB9FyVZRXAke6P+S3WW1lsFtlY5aonlnQUUJera1oggukVdxQNdYiyjFCsvy0LvKtnIrtkBHrVSMH1sgww0IlVdWWaX1rkonsg637CI6ZPEtcJZUSTXFTqtVKrKD6aI/rtpy9F8S1SI7MQpXqVsuqqyukIplp7uCCkfJ6naoooornWXILw90LmHFIy2AgtyFsoSsiwUkftYaayHz5AC2qSAOSgwCNhcxTkilYA9kX0GAGmwQQ0ZQUWF1BrEKd3kBursEBRcEFqFYOYn/dTeEklRoL7CVB5FqpJXrAlkLKpDiIHsLXiEigVOzOggVoDTnryudReIjwISCXhvn2SCEzS3k+wY93iqjLOwMFSVHaa0riCNjKy7KK0RFnxycMi6r8GxcmAURKOOC77neFKqsTpcNfx3EpED5KTgqdpugRii9g4ATZUv0jal0yyhXXKfe62zJ6ip0wjsLYYvc5Q4kyuUuF99YDoUL1qJsyAj6LlVU2Zzog2S3rS2c4KqcME2ak5WZmpZnTs3Mm7NgyaS8nKzFFE2aMHmy6rxLdU1KUp2JUwNBA3BKAE4IuCcFJCQmBJwBysni7uIx3s0Pvt4RqH4bof6P0Ejs7qOyCKmv6iL36PF1P+5OIkdSw8Eo4AAUmlxHUR/mO1C4L0IahP9rUMPp1LAgB9xh/8v/g34Hg/Rdn0CbZswgOBcqWgrrS9hLO3YjX4M0jF6PsNkGolq4dAu9bsT+A6Vx9PoRfB0lTaHXQ3H4AdJser0L+/eXMum1fKOtn4S0mEOvH8D+eimfXjfj675SGb1+FF/3karo9XAsP1LaSq9fxv46yUev3TeB/AhpN70+iP3DpWf6kvdtjif1Nz19fxN1PCbw/aPJ3xaBOyjfK3B2XTc5mLd+R9pRjQJ//xzhLQKv/5rwvQLvonJaBf4YDd8p8Bcp7xJ4B+WKwPU9dFLdlGD+MQ2vF/hXlBsF3kt5nMCHnyfcJPB4yi0CT6LxyRf4NBq+VOAZlNcJfAnljQK3Mv0LfB0Nv1fgpTQ+rQLfTMN3CryZhu8S+IM0vCLw3ZRLU4V0pFwv8NcpNwr8fcrjBP43pn+BdzP9C7yH8nyBR1+g+hd4f6rPOoEbafhGgV/9iupf4PE0/F6BX6DhWwU+g4bvFHgr07/AU2l4ReD3UC5NC+ZrKdcL3EW5UeCNlMcJXKHxMQn8URreIvCnKc8X+EGmf4FHf0/1L/AOpn+B72H6F/hHTP8C3870L/AvmP4FfonyLoH3u0j1L/DhlEt3BfPbKdcLPIG+r1Hgs2n4OIGX0vAmgS+l4S0Cb6bh8wXupOFLBd5EeZ3An6e8UeDjmP4FfoCG3yvwDyhvFXgnjWenwL+k4bsEfo3pX+AXqBwpKZjH/ED1L3AT5UaBOyiPE3gL5SaB3/QN1b/AT9Lw+Umhv5ulApechNcInH2P6zTktAj8KOV7BR79NOEHxfei8luTQn+vuwS+n8pXRL6e8B6Bs++9ND30990o8BYqP07gFyoJTxI4qx+YpoeuD+QLfCfTvyi/iepf4Kw+UTc9dP2hReBbmP5F+c9R/Quc1T9ap4eub3QJ3M30L+rtGap/gbP6ijQjdP3EKPBJ1J7jBN76MNW/wFn9xjQjdH0mf0boekupwJufovoXOKsP1WnIaRF4LtO/wKVyqn+Bs/pT64zQ9aUugWcx/YtynqD6F/XG9J8cun5lFHgqs38x/ONU/wJn9TNTcuj6WL7A72L6F3j+Tqp/gbP6XF1y6Ppbi8Djmf7FeO6g+hc4q/+1Joeu73UJfCTTv8BNVH6PyKl8aWbo+qFxZuh6YJzA99up/gXO6pcmDTn5M0PXG0sFbnyQ6l/grD5apyGnZWboeuZeMZ40/gcFzuqvrRpyugT+JeWKKGc71b/AWX1XSgldvzUK/GMqP07gXduo/kXO9J8Suj6cL/D3mP4FHk31UyNwVp+uSwldf24R+DGmf4E30/gfFDirf7emhK5vdwn8daZ/gTvuo/oXOKuvS7NC18+NAv8907/AW8uo/gXO6vemWaHr8/mzQtfbSwVeR+XXiJzpX0NOy6zQ9fy9Au/aSvUvcNZ+aNWQ0yXweqZ/Uf5Gqn9Rb0z/s0O3L4wCr2H6F3gzlZ8kcNY+Mc0O3R7JF3gx07/ATVR+jcBZe6Zuduj2S4vAc5j+BX5hA9W/wFn7p3V26PZOl8DTmP4F3kLl94jvReVLptDtI6PApzH9Czybyk8SOGtfmUyh21P5ptDtplKBR1P5NQJn7bE6DTktAr+F6V/grfdS/Quctd9aTaHba10CH8j0L3AHld8jPpfp3xy6fWcUeATTv8CNbqp/gbP2ockcuj2YL/Bvuqn+BX5SpvoXOGtP1plDtx9bBK5Q+XsFXkflHxTfi8pvNYdub3YJ/CyVrwjc4aL6F+NJ5Uupodun+ycSDjsv9efm9RzkeDzHWzk+geOdHJ/H8ZMcz+b4aY4v43jjJMJj6bWF9RMLPJH1Wwv8MRZ/gTeyeAq8jsVH4HEsPQXO3qFH4Gw+hX5yMGdzymIErs6z0+BJAs9nHgmE96VzMNk/PcfDOR7N8QiOx3Bcx3EjxyP5eHK8D8cTON6Xjz/H9Rw3cbwfxy0cH8DxbI5HcTyX4wM5ns/xQRwv5biB4w6O8/PkajjOz3ur4zg/T66R40M53szxYRx/jOPDOd7C8Rs4vpfjIzi+n+MxfP7l+I18/uX4TXz+5fhIPv9yfBSffzk+muNdHL+Z4wrHb+H4BY7z8y97OH4rnzESA5yfN6nn+Bje/jnO57EYjo/l7Z/jt/P2z/Ff8PbP8Tje/jk+jrd/jt/B2z/H7+Ttn+Pjefvn+ETe/jmewNs/xxN5++f4JN7+OT6Zt3+OT+Htn+NTefvn+DTe/jl+F2//HE/i7Z/j03n75/gM3v45nszbP8dn8vbP8RTe/jk+i7d/js/m7Z/jJt7+OW7m7Z/jqbz9czyNt/9JAZ7O2z/HM3j75/gc3v45buHtn+OZvP1zfC5v/xzP4u2f4/N5++f4At7+Ob6Qt3+O8/WHXI7fw9s/xxfx9s/xxbz9czyHt3+OL+Htn+NLpev/kdlHLmltrWx1SXcvXDRv0ZIFeehvWkbe3easrFRz2jxpYpG1aqKrtFz1X7I4I8+yZE5GTlaqNFEud0gTXbWuicWuiYUlzkq3Y2K5tbzSWTuhvKBGw6fQ7XTClMiMpXen5y3KXDAnL92cY+Yu0S9jcY4GzVh4txqV9IzUJXMk2em2SnR+2UqMVhsz8ASwov5SfDzMAYovL3CkqLctWDI/b8HC9IzFeCreDONYFwpGlZEScCZwbiSgBi7ttgqrS3UkqC7mj1WpOhJUV+D+cpsMDpiSV+nGzhKn1VpUixzWmoJCmchDV9TXJRfZKuA1KlVnkRWJScGsCJ42toi9PkxYkrC2sjOzM/LSzNnmtMyc5dJYu5vg1OU5GYvz5ptzpSBNZy7NXLxwkTQRZppCMuGJh/Ot5eaqApsdNDkDPWQGktJfWpSRnbWc3A06zMtMpxdIqfMys7IWq2pelJGzaHleVub8zBwap4XoKQsy0lFhTyJjzkmzIAG5krsCz1KzFkljXRPGutH/iUMqctZy8hYvmY9sb+GizBULF6SMtUN0BM+55jlzMtJT4qTbwHsG/Oc2o1Q1ecKkCYlIYf/D3tXHRnmk9933Xa+dXXjj3HHI3HHXSRqQubBgiEMRcRLW3l2vvxfbGIPx2Yu9a2+wvY53DSYiJ3JLN2m7tlHLUZRrFJJYadTLSbTHRanSnlBJ3bQ1a05NoyqKdLSiaU5CKVUJx1XpTn/ztV/2ayqlf1StX7H+vTPPfDwz88wzM7vPPDATz6qqPY9V45+lJXiC7NxBdlbt3GVpjoxNTlmmdu9y7ap2HXsUDB0dYwaNXcKobA+BkDgstcxGEe8sxCPaOniICLJ7YmB4TzZUFx0dj4yEJvbwkG8kOBTbo2j1kTjxB2PDgqYGbzIW6huIT4nOOYCOjYwNWAZDA/m91dHc1tkhIlrcjRgz8drQilfMlLZ2j7edD76Fm6ZWhge3ks3HgiNbye4tlnwjzG0Dlg6vt6mvw9spXrytHsjJyCD/k2MqMjY+yc2Xs8Z7JAyhCA3yeaMsP/uO514n8l6PW4SFqOxPMhDFlBsTeZUVaM7Cc4mtZ87Ic6l1Z86ss8Ces8CQc4kF51LTzaU2m3nGmvlWmsuZZ+bbZeZbP2ZNBfNMMHO2l/lGl3nWlgW8FdhXLjGsXGpRmTOlzLOhzBlP5ltNFphLFttJ5uwhlzGELLSALDZ9XGLzWGzsmGflyK3W8wVpqdLqq9vfLs3I8xNCz7hJp7fZ28LUC6ms8+9vberY4rB01LnZiuDu9FsOQClgGohAZ0OLt21/pyXQ1tzc5+3ytkLeA+4DrSLC3V6/I/u209LZ7g70sWWvoR4zymvpCMUJRmDg6Hg0MhYnrItCFg+auDS2uPWkh2v+XosnxIzm4yQeJaKzLB0nxgaI6FISDYeZYXxBz5Ka8OCTlnbe9WQ8OBGPBEdI/hAUjIpIHcCQEZ8nBlUWi5ORaHCQTZJYzuCV9HS523stAWYjTngvxvnlhDhUbMdw9DhhFtiDBBHIGg9aOkTX8/c6MfFzksSHr8bd3n6y3fMk6TmAgn0YIszvMUzCfBkkNT6kqBkYBY8dEE/CpTYnrpyuKsijFWicGrCOJkLyI1AGRE4y3gifnCI80CAnTwemE0FJHXyOEWVjnzfvRLWHQhNRF5uSJH8O84gayAz4bmhlA8EnsBoB98BRciSIWrODJtvI9C8yWZqjQ/lsSiZkDXVCgRCpQA5w3VLYb0LfkB6o/5NQ/73IA12UXydXTnJA2yfHyORYJBwJDYphVWqMEXjEwDDUL1GKJRsdj2KaS1Ylc/lljYSGggMnSIFSlAEucaRH3gIZZCLOdS/h1v0NkOAIv1zDw+R4JD7MGhiODOV0NunxNbvrO3qX6nUUDkmSY9MZnCJ1JDAyORQZI14sDJP8jo4vCHnGcjnhQjYIKVYRlikn7Hx/y7ef2L5CjGPsPR4a3c62TPzPpsHtA+OTPO1y6UBjn6rtA0GI13beeY9uj7EbQ9ln2e2t2uXynR6a2id21/dMPxkLDoUK08sleA9hvR5liojd+CBy38f7FSJJ2PLI+jl/FSThyITshXv1w+T2QXRCcGwg27JsveI+i9S+ZHByIlsN1//ZdHJ+ET5bMT4qR6XPQ3g/EBDYXZ+nthSUb5KviA+iNvU+USr06DikQcoz2SRioBsIaw/CjsL8KrucalEm4hCYcRQ1rjSKzLmVDIbCwUl2EWWIlaqmRxUvsmiv2dHpwXQXW2q5G5Vf++zatmOb2FhWPbbjMVLZjqr8wTgRBNdO+SWLq+1R4gqPxKNPBCdRmSvM9/gTERwCMH2CMcaEiAxh0xSPDLigukMTfDVhveUKR9G3rvBEcDTk4ksRmsczjAbjwy5+rw3hOM4XrpFodNwFnVEQPAbB4uUEGuqI68DIVlfbDoGuYMw1hmMJGOfh2tiJ0SNRLAgkf1y87e1t7b17iLgclLdKOwrHL5cOxSxJVjxOm2J7NnFycUrHE1/2ERX+DxVjaeVCM0kq2cKEly3gdGSSBGNsiUHPneRBdqYKxWLZcAP2C1GoORHi7+i6iegoVj9RsOvLPpK/zmgcsls3EY3FXB3RgaPYy3ROsKt2A4JRvi7ESOWmbTvCmzZtyf6k8uX7RxTVOREZGoJIDo1Ej7BVeDQ0MRQaw5oitoDF20NSMxydiDwbHcPS8nQQOQe3bdvGfPQU7TNJDZutWG8jg1NsZzEWx9+jkZGRmPzSK7uFJTVqiUIKtnaxm4F4ZQssf81LL/fDpMcVP+mKnnSNnnQNnXSFT7qCvVmzx9wemm8M1B6hzefD32YvYnr4cac3Lz3f2ssNAk/Yc8Dvba3z9srlW6UTWwyRLuDrPsn3P0idPRr35p8CkAZ7ZbbnaGgG9OCc3Lv0JENqZCm8x/oivBtyPcKXkSctS89ES/Pl2pN3mMIIjPFUWIXyCiQ9WY7l7+Bsq0wiYcLWaBKJkSORseDECRKdIMPBGIkNh45gYbPkDntif1GDiYG//NsOxngUf8JjYKWDNUEVgtMkkWMCHRqJozz+NUlWbnKnyYJi2YaU9AQnhmJSyiyW/SPxiaArzPYWIbXVwP4cAShWtoXjVUZCsXx5YCmX5XdpBerAW5Cc31VlI8iy9RZ8P6e+etsuFST7tk29b+vu7i61l9h0zWo5JZ/i7/fuN9aucTruK1PpisPPv0opeW35zyl8xl8zp/93PsX5k6gvx93BvT+pyND0VzOUIfu8gs+eDSKu+BPYsJSm8j+yIZf/EZP87DNdRKMVhbjS5yfLpPnTvPJ+USE+K5XxkQn9axvEh/F/fMPK+d/LK0O9fyTrfmWF+l+R9Nc3LM3PcM3XM/QOaP9iUv/PEP8Q0lSuz9A/+EruswHhz76WoT/H5y1JOwwcQ9izMUNP4PPZA7nPIRlmNPb+4kbxnp+m+PP3KM/6Df1xvya+/79hy9BBvFc7MnTdVyyWS7+WoSmEbwMvAR9+MENvAi89BH51hB9GeuBcJfgDvrcFdGD82xnKfBZ0ujL0fWB8W4beBVbvyNC9JRaL7bEMfRNY/RtIz7AmQ2vsSP9Eho4AP3gyQ8+wG3Fu0IGeugwtL0V8X4ayO3Zzkxl6HnjjRIZ+Cux8J0Ory1D/r8AP0PZVSueAt+sp/Ri4zk/pLeClVkr33mexnN1H6Rng4CClZVhS1x2ltBsYH6X0TeAl4PtA2xilnwI7gWVO1AusBN4G+oE3nqH0LIuPUXqZxQOvAwcnKV23BuUdo7QZ+B5wBLjuOKUp4OBJSsvXoh5gFdD2HKUBoAc4DjwLPAO8AbwIrP4updeAp4G3gB8Ayw1ggtLdwMHTlB4GrkuBf+CNWfANPH0GfNyPdMDq+9k9Rkr7gdW/B75ZPPAysPMspTeBl76PdOXI9wNKB4FnXwYfLHyB0n8A2l6n1PMA4ucoPQ288UNKPwCefovS2w/kftu2PttusU6VW7+xprTsjFX85sp+N57SMrSKGRQY5T6jovF+5/GyU5anvv74tx99+CFl58B+zyLfzFD++6HbKE9qdUZFQq83yJBRgbDbKOO/OTL/f7uR7hFmABExqrqSeiCl+RO2p694F3rnjTKvUZWwJfWUNnxlQTuICPFb4hz7vepbGfoCd5NuVHln9LaETWt1GGWNzsZZbXTRw/N2GGUtRtWspv2WY7HeKfJex+c05kJU5CXepN6CvIEZTetIt/ASDuBvg3PYKPMbZEbbnz46o3nTjN+NyPMOydBnmaGFPmY1iDZhlGkzBjkC+EeDNBtlBxH5XaMsYJABxi7/La2T1bUpQ/n/F1BrlM9qtUbFjF5rkGmb16hMlbiNqqTdbexOlNYb107ZtF6HsRtxbqMSaZAWeWrRIqf8jW8O5VxDea9ZRHnTmteoSOloTdLmMSoTJfXGXi3sMCoR41a5m5wg+fMiLJYU+90SZVVvzlDm78jyHcZbc5a32ixvdYK3fu33jbIr8wtX04sBoz9RmrSnSqZtM/qs1mrs9i1huG7ZpNp7aF3dksRuJ/9d/BT4OA1d9E3WV41Mdrxr7dpfQArb5gNr7Ah3OhBodko5u4j0ceisdxn/B4zrWkuipClpC8zo2oFZTX/IuuhHle2ORZ/Tv9jnuDKfZlVpnlntsGPRjziL8Fl5F/lvPgJ9r/NyLuudidKWpP1wqgQl1aOkndbFpmkbypq9um9xBC1DQR6kE01jDTswbdMiVxejs1rDtC3guOpn5TNoch6+yipivyP3o/zO7Rn6oKbmRsda+zOpkq6E3Tdti87o+q9bHVc8C56rnrQbDfU7NV/awyNYkMvTnM7sDzL0C5vqo7q19tppvSllS5RALh08X8BxpXah9qp7HqEmp37GCmQD4kcvJkqSWso2rQtbhNvAW9Dn68WcCHTwCRBIaNoLjisNzh7HFT+Tvk7HlU4nO+Myz/fXd2UoN1VDGxIY/n7toMMor+NSynyM+pGmZneGbtKEjM5oUBfTTK5StiajMsnkKmH3GBetetLq4NLgzpMGNLsTsb7CWExiVv8cuym+J0O5iS5kXBtIagld++Mr3nl9o9UoY33E1qytWJOe37h0znG59mTnXMC48LD+49Jl55zbKe0jKqDzRrohH8zIZx/rc/9ae8OsPmObLknZE6X6WyWs22uderXGXlhGxkeArZVj4JWNVTvjo95sfjUaF563seEzm/xs7l9AebefwR7iSTX24MMn+PBxRsptkpGL5XLE04s+NualGHP7dMmMbVaOO1u3Ky5maMSd1yZZ1j5e1pSh2sJsLDZiHe/+N6zzG5TsNq61d+b1wSCv2uvU/7BM5NO6GDY6RR8eZvkdlP6MBZplfR6Wv54V0IYSfrtCCK/+gwdECfzuPvMT8BSlyv6J9eubiNuIuJeZEVuLWb+6Rb+eeVDv0My0jijvLsoZ8YI3baVxkuWd+p5Nf0RbdpxqncI3rR97mi+wd/lrZlwWMM6saUHGpL0pVXKQa5GPoVb60iP4++dprdnBhmmRjbLWjKjP021Czy6ynPnKszs9Bfq/OtL7nNr5tOaf0WOOdAuEbk1atOMy20sdovS1FfulLtsvW+7RL+Vsz9WPvZVmMo8K1y5d/yeraYFsKvazPd4RSp+yKN3RYJBnuObg9FOg3wDdm0evOp6jX2B7wQFz+mXQPSvQr4MeN6Fz+xnsKedA/1Tolr2NCXvjjDaRsiVLGqZ17XfnvQveq4egioy9yRKmQvVyKwaqWwS0Vzld2pA1oyx/mNJ3hF7tb4PatU042Fq8b1pL6doPHUjc5uT7KqT9eGh5vpj913nQ1wxTGrQqvkoapzWtIWlrTelR7JbAUxN4sqX08QWpsxZY/RFK10i93pawJ0viXLnvS0GcmiCHk2Ah7V1scXo58j6yYb9Mnjbvw4dBD5jQ2UHbA/op0D0lvN5T1jYmwsdRsc85LNZK/QWrqLje6RUvDU4v1s+/vdotgq3OwLRNL7M6rmJO1LN+YrFeZyj3qtWpV1GmbIGQM7b3b46at4GdCU6uQGdnhbdAfzyfPpqjszPEwgr52dniixXow6BvHTenvwj64RXob4KeMqGzPfj7oP8Z6P9hy+7B19pbpnW2RdDeYbq1nq/lt5DuLM46swXzUSzltXLNYecgC84/f1SaV1YgUdowXdI1YzuUsjfO6vqcdcGz6El3swUAq03KztYZfZPmWPCkPdgCSTu9fnZ2wpmI77PqjQvWxkTpoaS9db4bOgLBpH2IjSbTkbqhOzCdGq/60/5Ftv6xOXUB+W+fovT7WX6xkGt+wbDfuU+8ePicWkDa4eeX7yNW1k3Qz4N+OXtO8bFzCiuw2WFU1PGTCipm868CZ7at36P0JTGXxvlcFiK9j+9qzzkgfM1OrYWhz8nnP/Kcx/nubHH5Aa0/Wz4UI0s7hbRrcAZ8rqBdPWpPtU9wLfa8c0jbj7T9Uhe0JTGoUq9wXuKCh3YHn1dtgjMZ6hJzhK//KGfqNyn9GzFPq9qSesJ2ZEbTj+rpQ7xp+jXrjBZMS322EefRit/BuVVT+gSHM73UypOO4gT1vCPd6IylGY9+pP0CZ9lfaKq/oAK6Z/RAupcdrMZn9K5pW6oEzH6uZrTPqb3E3xe9aXZcswwzu1OUM4ez8DFV5wx23FPTNmzMtX1JO3bm7Ua32+jvY38DWOy664x+pGOLJ2qqMwJi8URFgXnv4gmU36JivBAvVuve+UUum18YzE8PVefKQNu0LVH6naR9dFab4ueAOaZhkKc+affOo3SfKJ31OVsra3D+LsN5vJYbaRrXrPtTJYnS5xxs4zqUtEup3qM55v1cpuud+kdWFWh16k9kKV4uvylW3kvFsp7iosDob4H+Iuivib4p11/WjOx9ESb/oFfc/U/6Y3ao78IJLVGqeXN7CX3WjulVz/v+4BV2mtmdv9UQ5dikPTcTkfrW/cx702Vbni26JsOlltVn9Vl9Vp/VZ/VZfVaf1Wf1WX1Wn/+bD5VP9j6cPHgpf63F/lnVHe9fykvXxf+Xh7oTvSDPXeoudPWPRE513lJ+Y9XdXlWOugOs/MSqO77qPPh5hkYFg6I8dSe8/KcirO6Cl/+JCCuDtx/Jg526y63uJqs76J/K+//qrvp5mV79jqzOhequ8+Wfi/LvSH7KJYO/lOHr27WCfJf/ylrQDsXAfUX8fCt7HhVPhoryLs9b1XhF88fhlgz/9C9FzK9k+LP/ZXJ20aUtG2+XA7Be4maJuyT6JHZJDEs8JjEp8ZzENyS+LXFe4ocSP5F4R6JdOhtYL3GzxF0SfRK7JIYlHpOYlHhO4hsS35Y4L/FDiZ9IvCPRLgV4vcTNEndJ9EnskhiWeExiUuI5iW9IfFvivMQPJX4i8Y5Eu5ww6yVulrhLok9il8SwxGMSkxLPSXxD4tsS5yV+KPETiXck2uUEWS9xs8RdEn0SuySGJR6TmJR4TuIbEt+WOC/xQ4mfSLwj0V72/0O/F+t59Sh/2sp/Z/Gj/Gcr/5vFj/KXrfxnFj/KP3bWH3bRo/xh3zTJr/xfK/+TxY/yd73bpHzl39prkl/5sw6ZtF/5rx42KV/5qz5jQlf+qc+Z1K/8Ub9rQlf+pz82oSt/03dN6Mq/tMOkfcqftPLft6R/Jf2WCV35i75s0n7lHzrrD7roUf6gYyZ05f/5U5Pylb/nV03yK//Oyv/bEvmU9NdN2qf8N8+a0JW/5n83qV/5Z876Yy56lD/mKhP+lP/lYRO68rd8xoSu/CtPm9Sv/ClvMWmf8p/8dyb5lb/kfzahK//It0z4U/6Qlf+q4kf5P75gQlf+jq+Z0LN6TfozVqmUH2Mzvace5b9Y+StWqZWfYjO9mN33yPzKH7FKrfwQm+lN9Sj/w8rfsEqd/X8I7q6cX/kXVv6Es6mln9ab96hf+Q9W/oJVauUn2Ewvq0f5B1b+gFVq5Qd49z34V/5/lb9flVr5+fXeo36l15U/3+z4y/yhe4y/8t+r/PVmx1/mH74H/8o/r/LHmx1/mf/MPfIr/7vK3252/GX+c/dov/Kvq/zpZlNLP6Xv3iO/8p+r/OVmx1/m/6/Ozt63aSiK4s8OH1EpKBMLX5HoQJGwgrp1StshCCHEgmBrkjbClUoSOa5EmQI7IjNTEAwdqNSBiT+APwBWBhZEFqSIShUDovjjntf4qM5FeMiNZf/87vN1/dzj+PiLwsMft0o8fHB/KTzGLfjd2voLP6PUD+Ma/Gxt/YXPG/cwYdyrU/vwqR0rPPxp4Udr6w+fW6X+8J+F36ytv/B54yom+MuWKH/4yPYUHv6xA2ofPrEjJX/4w8IP1tZf+NdK+/B/hd+rrb/weeM6JozrfeLh4/pGqZ/1XX1G9Rf+pcLDnxV+rLb+wu8r/Yf/6oB4+KzmXVdggr9qlXj4qFaU/Qf/VPil2voL7ys8/FGHxMMHdaDw8D+9Rzx8Tl8o/cd1TYl4+JjOK/WDfyn8Sm39hf+stA9/0i7x8CH9pvDwH4XfqK2/8GNl/8FfFH6idm3x4cy77sIE/9A+8fAJHSo8/EHhB2rrLzxft9VWVhbL12p378+X/+kR6yK0w2gztaU5Z6Fx02qP+xePtENeByaBS6JLGq/nx69ybDSN1+6ELe9Re8tL3DJubKwbL3kW3gtbT6LP+DWWJlnuN3q+8da32/ELE5MYBukSOK9MzqxGy4LWZiNeUb51N6PtBZ3Ef8Nr+avJY96r/npwNDeRTjfodFtBuB0lkhJhs9dLc0tfh5nmhu/xOnEzUQNJco3HG2tRQp0w+UjbTreTbCa27Yktu4567jXCMNhoboX2acj/n86YrBfojpuN7Dd6guYvy7FzivRlxAsKv0X82M3Gykn6v5niHPHQyRF/vs0ex1Vq/zrx0MMRzyr5x7/dOzg87FgVVfRvxFk3q1OzrLUoNXBJH0eEcF+UPIukSy+LVu6S3o64Sz+c4rPCbdGuwUOvRgRwmvRvxAeihWMeejgieM7fjoOyT13S4xHRUd5/6H9X+GXS/xFxvwC+p8w/lbzQfv27k4nvzpMuQ/k/J372j5OJd9zpx8+A+IfyDbFEN3J4/72iv1+/5GZixUznd6X9giTWx/v9LrnHrs/3ld7LOuBx/2gg/FeF/2BS/92COZ4v5eSP+NEYebOkjP/CD3PyZ/4T+o/zn/A7Cm/HUTl3FOh+yp7wKAy3i36NqH34bO9dkf/Dlfx/EI/7ZSPh64Xp/AHxddEv6lclj3PTj//fqD+Wi384/ES5/sw7Tto+H6fgPXP8+QtxxqHfhq7J9ZPwt5Tz92TfM/qm8GVn+vnzL/em5gQoOwIA' 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' [s390x]=$'0 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' ) +declare -A b64=([aarch64]=$'0 137416\nmd5sum:08465cfcff2e7fd5c20162fb1e165e5b\nsha256sum:5d5c00624112f680f7ff66a99372f2e489dbb4f7de3a74d787caa57c54c3da68\034\035\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' 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' [riscv64]=$'0 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' 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' 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' [s390x]=$'0 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' ) _forkrun_bootstrap_setup --force diff --git a/frun.new.bash b/frun.new.bash deleted file mode 100755 index 9d60f69f..00000000 --- a/frun.new.bash +++ /dev/null @@ -1,1746 +0,0 @@ -#!/usr/bin/bash - -if shopt -q extglob; then - extglob_was_set=true; -else - shopt -s extglob; -fi - -frun() { -## bash orchestrator function for forkrun, providing extremely fast shell streaming parallelization -# USAGE: . frun.bash && printf '%s\n' "${args[@]}" | frun [-flags] [--] parFunc ["${args0[@]}"] -# FLAGS: [-j ] [-l ][-b ] [-k|-u] [-s|-U] [-i|-I] [-d ] [-E] [-v] [-h] -# HELP: . frun.bash && frun --help -( - # 1. WRAPPER LOGIC (Current Shell) - [[ "${1}" == '__exec__' ]] || { - - # Check if already setup (and FD is valid), otherwise bootstrap - { ${FORKRUN_RING_ENABLED:-false} && (( ${FORKRUN_MEMFD_LOADABLES:-0} > 0 )); } || _forkrun_bootstrap_setup --fast - - # Generate list of loadables to enable in the new shell - (( ${#ring_funcs[@]} > 0 )) || ring_list 'ring_funcs' - printf -v ring_enable '%s ' "${ring_funcs[@]}" - - for nn in "${@##\-*}"; do - [[ ${nn} ]] && declare -F -- "$nn" &>/dev/null && ! [[ " ${FORKRUN_EXTRA_FUNCS} " == *" ${nn} "* ]] && FORKRUN_EXTRA_FUNCS+=" ${nn}" - done - FORKRUN_EXTRA_VARS+=' FORKRUN_EXTRA_FUNCS FORKRUN_EXTRA_VARS FORKRUN_EXTRA_SETUP' - - FORKRUN_FRUN_SRC+=$'\n'"$(declare -f -- frun ${FORKRUN_EXTRA_FUNCS:-} 2>/dev/null; declare -p -- ${FORKRUN_EXTRA_VARS} 2>/dev/null)" - [[ -n "${FORKRUN_EXTRA_SETUP}" ]] && FORKRUN_FRUN_SRC+=$'\n'"${FORKRUN_EXTRA_SETUP}" - - # EXEC into Clean Room - # /proc/self/fd/ is safer than $BASHPID in some namespace contexts - exec -c "${BASH:-bash}" --norc --noprofile -c 'enable -f "/proc/self/fd/'"${FORKRUN_MEMFD_LOADABLES}"'" '"${ring_enable}"' ring_list -export LC_ALL=C -set +m -shopt -s extglob -'"${FORKRUN_FRUN_SRC}"' -frun __exec__ "$@" -' -- "${@}" 0<&${fd00} 1>&${fd11} 2>&${fd22} - - # (Exec replaces process, so we never reach here) - } - # 2. WORKER LOGIC (Clean Shell) - shift 1 # Remove __exec__ - FORKRUN_ORIG_ARGS=("$@") - - # # # # # SETUP # # # # # - local cmdline_str ring_ack_str done_str delimiter_val pCode extglob_was_set worker_func_src nn N nWorkers0 arg fd0 fd1 fd2 numa_map_str parsed_numa_nodes_arg have_taskset_flag last_conflict numa_map_str exact_lines_val array_var resume_file order_mode unsafe_flag stdin_flag byte_mode_flag dry_run_flag checkpoint_file prefer_external_flag NORMAL_EXIT_FLAG c_plugin_arg - local -g fd_spawn_r fd_spawn_w fd_fallow_r fd_fallow_w fd_order_r fd_order_w ingress_memfd fd_write fd_scan nWorkers nWorkersMax tStart - local -gx LC_ALL - local -a fallow_args - local -ga fd_out P order_args ring_init_opts - - LC_ALL=C - set +m - - if shopt -q extglob; then - extglob_was_set=true; - else - shopt -s extglob; - extglob_was_set=false; - fi - - # --- HELPER: Expand units (IEC/IEEE prefixes) --- - _expand_unit() { - local val iec num p - val="${1,,}" - iec=false - [[ "${val#[+-]}" == '0' ]] && { REPLY="${val}"; return 0; } - [[ "${val}" == +* ]] && { iec=true; val="${val#+}"; } - num="${val//[^0-9]/}" - [[ $num ]] || if [[ ${val} ]]; then return 1; else REPLY=''; return 0; fi - { [[ "${num}" == "${val}" ]] || [[ -z ${num} ]]; } && { REPLY="${num}"; return 0; } - [[ "${val}" == *i* ]] && iec=true - p=0 - case "${val}" in - *k*) p=1 ;; *m*) p=2 ;; *g*) p=3 ;; *t*) p=4 ;; *p*) p=5 ;; *e*) p=6 ;; - esac - if ${iec}; then REPLY="${val[0]//[^-]/}$(( num << (10 * p) ))"; else REPLY="${val[0]//[^-]/}$(( num * (1000 ** p) ))"; fi - (( REPLY < -1 )) && { REPLY=$(( (1<<63) - 1 )); printf '\nWARNING: value expanded to larger than maximum int64. truncated to %s \n' "$REPLY" >&2; } - return 0 - } - - # --- HELPER: Parse Ranges (N, N:M, :M, N:) --- - _parse_count() { - local type val v1 v2 - case "$1" in - lines|bytes|workers) type="$1" ;; - *) return 1 ;; - esac - val="$2" - if [[ "$val" == *:* ]]; then - v1="${val%:*}"; v2="${val#*:}" - - _expand_unit "$v1"; ring_init_opts+=("--${type}0=${REPLY}"); - [[ $REPLY ]] && case "${type}" in - lines) byte_mode_flag=false ;; - bytes) byte_mode_flag=true ;; - esac - - _expand_unit "$v2"; ring_init_opts+=("--${type}-max=${REPLY}") - [[ $REPLY ]] && case "${type}" in - workers) nWorkersMax="${REPLY}" ;; - lines) byte_mode_flag=false ;; - esac - else - _expand_unit "$val"; ring_init_opts+=("--${type}=${REPLY}") - case "${type}" in - workers) [[ $REPLY ]] && nWorkersMax="${REPLY}" ;; - lines) byte_mode_flag=false ;; - bytes) byte_mode_flag=true ;; - esac - fi - return 0 - } - - # --- HELPER: Display HELP --- - _frun_displayHelp() { - case "$1" in - --usage|--help=usage) - cat <<'EOF' >&2 - -USAGE: . frun.bash && printf '%s\n' "${args[@]}" | frun [-flags] [--] parFunc ["${args0[@]}"] -FLAGS: [-j ] [-l ][-b ] [-k|-u] [-s|-U] [-i|-I] [-d ] [-E] [-v] [-h] -HELP: . frun.bash && frun --help - -EOF - ;; - *) - _frun_displayHelp "--usage" - cat <<'EOF' >&2 - -# # # # # FORKRUN V3 FLAGS # # # # # - -### DATA PASSING & DELIMITERS - : Pass arguments fully quoted via cmdline ("${A[@]}"). (no flag needed) - -U, --unsafe : Pass arguments unquoted via cmdline (${A[*]}). (WARNING: This flag forces Bash AST array expansion. Do NOT use this flag to speed up external binaries, as it disables the ultra-fast C-level vfork engine!) - -X, --external : Force external binary execution to enable the ultra-fast C-level vfork engine, which is FASTER than parallelizing the equivalent builtin command. If a command exists as both a builtin and a disk binary, this prefers the disk binary. (NOTE: If -U or -i or -I are used, the ultra-fast-path is disabled, and this flag has no effect). - -s, --stdin : Pass data to the worker via its stdin (instead of via cmdline arguments). - -b, --bytes : Byte mode. Split the stream into N-byte chunks instead of using delimiters (implies -s). Supports standard prefixes (e.g., -b 1M). - -z, --null : Use NULL (\0) as the record delimiter instead of newline. - -d, --delim : Use a custom single-character record delimiter. - -### OUTPUT MODES - --buffered : (DEFAULT) Buffered / "atomic fan-in" mode. Output is stored in a memfd and printed once the whole batch finishes. - -k, --ordered : Ordered mode. Same as buffered, but output is printed strictly in input-batch order. - -u, --realtime : Unbuffered / realtime mode. Workers output directly to stdout. (Can cause kernel lock contention on massive streams). - -o, --order : Explicitly set the mode (buffered, ordered, realtime). - -### WORKER & BATCH SCALING (Dynamic Ranges) - *Syntax note: Options accepting : allow you to define the starting value and the upper bound for the dynamic PID controller. Setting and to 0 or -1 has special meaning. Examples: 1:0 (DEFAULT) (start at 1, scale to default max) | 0:-1 (start at default max, scale to maximum allowed) | 4:16 (start at 4, scale to max of 16).* - - -j, -P, --workers : Set the number of concurrent workers. Supports : (e.g., -j 4:32). Default max is the number of logical cores. - -l, --lines : Set the batch size (lines per worker). Supports : (e.g., -l 10:10000). Default max is 4096. - -L, --exact-lines : Force exactly N lines per batch. (Warning: Disables NUMA topological stealing to guarantee exact counts). - -t, --timeout : Set the maximum wait time (in microseconds) for a partial batch before flushing early. - -### STRING SUBSTITUTION - -i, --insert : Replace {} in the command string with the inputs passed on stdin. - -I, --insert-id : Replace {ID} in the command string with [{NODE_NUM}.]{WORKER_NUM}.{BATCH_NUM}. {ID} is unique per batch, and can be used to redirect output per batch. - -### LIMITS & TOPOLOGY - -n, --limit : Stop processing after exactly N records have been claimed. - --nodes, --numa : Control NUMA topology mapping. Nodes that do not exist will be skipped (excluding for @N). - auto (default): Autodetect all physical online nodes. - @N: Oversubscribe / force N logical nodes. - 0,1: Explicitly bind to physical NUMA nodes 0 and 1. - 0:3: Explicitly bind to physical NUMA nodes 0 and 1 and 2 and 3. - -N, --dry-run : Dry run. Print the generated command strings instead of executing them. - -v, --verbose : Increase verbosity (prints timing and flag summaries to stderr). Implies --stats. - +v, --no-verbose : Decrease verbosity. Disables --stats. - -V, --version : Prints forkrun version number - --stats : Prints NUMA statistics to stderr (currently ignored for UMA) - -### ERROR HANDLING & RETRIES - -E, --retry-nonzero-exit : Activate auto-retry machinery for commands returning non-zero exit codes. When active, `|| exit $?` is appended to the parallelized command, meaning any non-zero return triggers a worker kill and batch retry. - *Note on subshells*: When parallelizing functions that spawn subshells without -E active, - failures must be manually guarded to return 200 to trigger the retry machinery (along with - 137 SIGKILL and 139 SIGSEGV). To protect the entire subshell, use the following pattern: - ff() { - # ... - ( - # all subshell cmds - true # <--- ADD THIS AT THE VERY END OF THE SUBSHELL - ) || return 200 - # ... - } - -### CHECKPOINT & RESUME - --resume : Resume a previously aborted pipeline using the specified checkpoint file. - - Buffered/Ordered modes: Provides "Exactly-Once" semantics. Ensure you truncate your output file to the byte count specified in the crash message before resuming. - - Realtime (-u) mode: Provides "At-Least-Once" semantics. Resuming may result in a few duplicate lines at the failure boundary. - --checkpoint-file : Specify a custom filename for the checkpoint file written on failure. (Default: .forkrun_resume) - -### UNSETTING FLAGS - +U, +s, +N, +i, +I, +E, +X, +v, --no-stats : disables the corresponding flag listed above, restoring default behavior. If both +flag and -flag are used, the last one passed is used. - -### ENVIRONMENT VARS - FORKRUN_RETRY_LIMIT : Controls how many times a batch will be retried before it is declared poisoned. 0 means declared poisoned after the 1st failure. A negative value means it will never be declared poisoned (and could retry indefinitely). Default is 3. - FORKRUN_EXTRA_FUNCS : Use this to specify required sub-functions to pass into frun's environment. - EXAMPLE: `hh() { echo "$@"; }; gg() { hh "$@"; }; ff() { gg "$@"; };`. If you call `frun ff /dev/null)" - resume_flag=true - - # If the user only provided the resume file (no extra args), inject the original ones - if (( $# == 1 )) && (( ${#FORKRUN_ORIG_ARGS[@]} > 0 )); then - - # Set positional parameters: keep resume_file at $1 so the bottom - # 'shift' safely drops it, then append the original arguments. - set -- "" "${FORKRUN_ORIG_ARGS[@]}" - - # Resurrect the bash functions into the current shell environment - [[ -n "${FORKRUN_EXTRA_SETUP:-}" ]] && eval "${FORKRUN_EXTRA_SETUP}" - fi - - # We intentionally do NOT call 'continue' here! - # This allows the loop to hit the 'shift' at the bottom of the case statement, - # which will drop $1 (the resume_file) and smoothly begin parsing the - # newly injected FORKRUN_ORIG_ARGS on the next iteration. - else - echo "forkrun [ERROR]: Resume file '$resume_file' not found." >&2 - return 1 - fi ;; - - # --- LIMIT (-n 100) --- - @(-n|--limit)?(?([= $'\t'])+([0-9+-]))) - arg="${1##@(-n|--limit)?([= $'\t'])}"; - [[ ${arg}${2//+([0-9+-])/} ]] || { shift; arg="$1"; } - [[ ${arg} ]] && _expand_unit "${arg}" && ring_init_opts+=('--limit='"$REPLY") ;; - - # --- EXACT LINES (-L 100) --- - @(-L|--exact-lines|--LINES|--EXACT-LINES)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) - arg="${1##@(-L|--exact-lines|--LINES|--EXACT-LINES)?([= $'\t'])}"; - [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } - [[ ${arg} ]] && { exact_lines_val="${arg}"; last_conflict="exact_lines"; } ;; - - # --- LINES / BATCH (-l 1k or -l 100:1k) --- - @(-l|--lines|--batchsize)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) - arg="${1##@(-l|--lines|--batchsize)?([= $'\t'])}"; - [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } - [[ ${arg} ]] && _parse_count "lines" "${arg}" ;; - - # --- BYTES (-b 1M) --- - @(-b|--bytes)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) - arg="${1##@(-b|--bytes)?([= $'\t'])}"; - [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } - _parse_count "bytes" "${arg:-}" ;; - - # --- WORKERS (-j 4 or -j 1:8) --- - @(-j|-P|--workers)?(?([= $'\t'])?([\+\-])+([0-9:])*([a-zA-Z]))) - arg="${1##@(-j|-P|--workers)?([= $'\t'])}"; - [[ ${arg}${2//?([\+\-])+([0-9:])*([a-zA-Z])/} ]] || { shift; arg="$1"; } - [[ ${arg} ]] && _parse_count "workers" "${arg}" ;; - - # --- TIMEOUT (-t 5000) --- - @(-t|--timeout)?(?([= $'\t'])+([0-9.+-]))) - arg="${1##@(-t|--timeout)?([= $'\t'])}"; - [[ ${arg}${2//+([0-9.+-])/} ]] || { shift; arg="$1"; } - [[ ${arg} ]] && _expand_unit "${arg}" && ring_init_opts+=('--timeout='"${REPLY}") ;; - - # --- NUMA NODES (--nodes auto) --- - @(--nodes|--numa)?(?([= $'\t'])*)) - arg="${1##@(--nodes|--numa)?([= $'\t'])}"; - [[ ${arg} ]] || { shift; arg="$1"; } - [[ ${arg} ]] && { parsed_numa_nodes_arg="${arg}"; last_conflict="nodes"; } ;; - - # --- ORDER (-o buffered) --- - @(-o|--order)?(?([= $'\t'])@(realtime|unbuffered|buffered|atomic|order?(ed)))) - arg="${1##@(-o|--order)?([= $'\t'])}"; - [[ ${arg}${2//@(realtime|unbuffered|buffered|atomic|order?(ed))/} ]] || { shift; arg="$1"; } - case "${arg}" in - realtime|unbuffered) order_mode='realtime' ;; - buffered|atomic) order_mode='buffered' ;; - order|ordered|'') order_mode='ordered' ;; - *) order_mode='buffered' ;; - esac ;; - - # --- DELIMITER (-d x) --- - @(-d|--delim|--delimiter)?(?([= $'\t'])*)) - arg="${1##@(-d|--delim|--delimiter)?([= $'\t'])}"; - if [[ -z "${arg}" && "$1" == @(-d|--delim|--delimiter) ]]; then - shift; arg="$1"; - fi - delimiter_val="${arg:0:1}" ;; - - # help system - -h|-\?|--help|--help=*|--usage) _frun_displayHelp "$1"; return 0 ;; - - -V|--version|--VERSION) echo 'forkrun v3.2.1'; return 0 ;; - - --) shift; break ;; - - *) break ;; - esac - shift - done - unset arg - # --- AST MANIPULATION FOR BASH FUNCTIONS --- - declare -F -- "$1" &>/dev/null 2>&1 && is_func_flag=true - if [[ -n "$1" ]] && ${is_func_flag}; then - local func_def body body_start body_trimmed test_body - func_def="$(declare -f -- "$1")" - - # 1. Extract the contents inside the global { ... } - body="${func_def#*\{}" - body="${body%\}}" - - # Trim leading and trailing whitespace - body_trimmed="${body##+([[:space:]])}" - body_trimmed="${body_trimmed%%+([[:space:]])}" - - # 2. Check if it visually starts and ends with parentheses - if [[ "$body_trimmed" == \(*\) ]]; then - # Strip the very first '(' and the very last ')' - test_body="${body_trimmed#\(}" - test_body="${test_body%\)}" - - # 3. THE GENIUS CHECK: Ask the Bash parser if this is valid! - # We run this in a subshell to keep the environment perfectly clean. - # Explicit newlines prevent trailing comments from breaking the brace. - if ( "${BASH:-bash}" -O extglob -n -c "function _frun_syntax_check() {"$'\n'"${test_body}"$'\n'"}" ) >/dev/null 2>&1; then - # It is a verified global subshell! - # Strip the last ')' and inject 'true' safely inside it. - retry_nonzero_exit_flag=true - body_start="${body_trimmed%?}" - eval "${func_def%%\{*}"'{'$'\n'"${body_start}"$'\n''true'$'\n'')'$'\n''}' - fi - fi - - unset func_def body body_start body_trimmed test_body - fi - - ${extglob_was_set} || shopt -u extglob - - if ${verbose_flag}; then - tStart="${EPOCHREALTIME//./}" -toc() { - printf '\n%s finished at +%s us\n' "$*" "$(( ${EPOCHREALTIME//./} - tStart ))" >&$fd2 -} - else -toc() { :; } - fi - - : "${nWorkersMax:=$(nproc)}" - - # Resolve Default Modes - [[ -z ${stdin_flag} ]] && { - if ${byte_mode_flag:-false}; then - stdin_flag=true - else - stdin_flag=false - fi - } - - if ${stdin_flag:-false}; then - unsafe_flag=false - ring_init_opts+=('--stdin') - elif ${byte_mode_flag:-false}; then - : "${stdin_flag:=true}" - ring_init_opts+=('--stdin') - elif ${unsafe_flag:-false}; then - stdin_flag=false - fi - - ${byte_mode_flag:-false} && ring_init_opts+=('--lines=x') - - ring_init_opts+=("--delim=${delimiter_val}") - - [[ "${order_mode}" == "realtime" ]] || ring_init_opts+=('--out=fd_out') - - # --- NUMA Node Discovery and Topology Mapping --- - : "${parsed_numa_nodes_arg:=auto}" - - _forkrun_build_numa_map() { - local req c - local -a online map parts req_list - req="$1" - - # NEW: Explicit Global UMA (No Pinning) - if [[ "$req" == "@0" || "$req" == "0" || "$req" == "uma" || "$req" == "none" ]]; then - export FORKRUN_NUM_NODES=1 - numa_map_str="" - return 0 - fi - - if [[ -r /sys/devices/system/node/online ]]; then - local raw; read -r raw < /sys/devices/system/node/online - if [[ -n "$raw" ]]; then - IFS=',' read -ra parts <<< "$raw" - for p in "${parts[@]}"; do - if [[ "$p" == *-* ]]; then - for (( i=${p%%-*}; i<=${p##*-}; i++ )); do online+=("$i"); done - else - online+=("$p") - fi - done - fi - fi - (( ${#online[@]} == 0 )) && online=(0) - - map=() - if [[ "$req" == "auto" ]]; then - map=("${online[@]}") - elif [[ "$req" == @* ]]; then - # Oversubscribe / Forced Count mode: --nodes=@N - c="${req#@}" - for (( i=0; i 1 )); then - local orig_pos file_size - if ring_lseek 0 0 SEEK_CUR orig_pos; then - if ring_lseek 0 0 SEEK_END file_size; then - local remaining_bytes=$(( file_size - orig_pos )) - if (( remaining_bytes > 0 && remaining_bytes < FORKRUN_NUM_NODES * 8192 )); then - parsed_numa_nodes_arg="1" - _forkrun_build_numa_map "1" - fi - fi - ring_lseek 0 "${orig_pos}" SEEK_SET orig_pos - fi - fi - - # --- Feature 2: -L vs NUMA Conflict Resolution --- - if [[ -n "${exact_lines_val:-}" ]] && (( FORKRUN_NUM_NODES > 1 )); then - if [[ "$last_conflict" == "exact_lines" ]]; then - printf '\nforkrun [WARNING]: To facilitate using exactly %s arguments per batch, forkrun will run in UMA mode. NUMA optimizations prevent -L from working properly, and will be disabled.\n\n' "${exact_lines_val}" >&2 - # Force UMA mode by re-building the map with exactly 1 node - _forkrun_build_numa_map "1" - else - printf '\nforkrun [WARNING]: forkrun cannot guarantee exactly %s lines per batch in NUMA mode. The -L option has been downgraded to -l, which guarantees a maximum of %s lines per batch. If you need exactly %s lines per batch, remove the --nodes option from the invocation.\n\n' "${exact_lines_val}" "${exact_lines_val}" "${exact_lines_val}" >&2 - # Downgrade to -l (clear exact lines flag so it just parses normally below) - _parse_count "lines" "${exact_lines_val}" - exact_lines_val="" - fi - fi - - # If exact_lines_val survived (either it was UMA, or we forced UMA), apply it - if [[ -n "${exact_lines_val:-}" ]]; then - _parse_count "lines" "${exact_lines_val}" - ring_init_opts+=("--exact-lines") - fi - - if [[ -n "$numa_map_str" ]]; then - ring_init_opts+=("--numa-map=$numa_map_str") - fi - - # Initialize Ring - ring_init "${ring_init_opts[@]}" - : "${FORKRUN_NUM_NODES:=1}" # Fallback safety - - # Create Data Memfd - ring_memfd_create ingress_memfd - - # NEW: Apply Checkpoint if Resuming - ${resume_flag} && ring_set_resume "$FORKRUN_RESUME_HORIZON" "${FORKRUN_RESUME_JAGGED[@]}" - - # # # # # MAIN # # # # # - { - trap ' - - status=${_ret_val:-$?} - if ! ${NORMAL_EXIT_FLAG:-false}; then - echo "forkrun [FATAL]: Pipeline aborted. Generating checkpoint..." >&2 - ${NORMAL_EXIT_FLAG:-true} || ring_abort - - # ALWAYS write the resume file! - ring_dump_resume > "'"${checkpoint_file}"'" - for nn in ${FORKRUN_EXTRA_FUNCS}; do - declare -F -- "${nn}" &>/dev/null && ! [[ "${FORKRUN_EXTRA_SETUP}" == *$'"'"'\n'"'"'"${nn}"$'"'"' () \n{'"'"'*'"'"'}'"'"'* ]] && FORKRUN_EXTRA_SETUP+=" -$(declare -f -- "${nn}")" - done - declare -p -- FORKRUN_ORIG_ARGS ${FORKRUN_RETRY_LIMIT:+${FORKRUN_RETRY_LIMIT}} ${FORKRUN_EXTRA_VARS} 2>/dev/null >> "'"${checkpoint_file}"'" - - if [[ "${order_mode}" != "realtime" ]]; then - local safe_bytes="$(grep -E '"'"'^FORKRUN_RESUME_STDOUT_BYTES='"'"' "${checkpoint_file}")" - safe_bytes="${safe_bytes#*=}" - echo "forkrun: To resume safely, truncate your output file to exactly ${safe_bytes} bytes," >&2 - echo " then re-run your exact command with: --resume '"${checkpoint_file}"'" >&2 - else - echo "forkrun: Warning - Realtime mode (-u) checkpoint generated." >&2 - echo " Resuming will result in some duplicate lines at the failure boundary (At-Least-Once semantics)." >&2 - echo " Re-run your exact command with: --resume '"${checkpoint_file}"'" >&2 - fi - fi - # Clean up memory only AFTER the trap is done with it! - ring_destroy 2>/dev/null - return $status - ' EXIT INT - ring_pipe fd_spawn_r fd_spawn_w - - # --- 1. RING FALLOW --- - ring_pipe fd_fallow_r fd_fallow_w - - # --- 2 & 3. THE PRODUCER PLUMBING --- - declare -a fd_scan_death_r fd_scan_death_w SCANNER_P - ring_pipe fd_trap_ack_r fd_trap_ack_w - - if (( FORKRUN_NUM_NODES > 1 )); then - # NUMA TOPOLOGICAL PIPELINE - ordered_flag=0 - [[ "${order_mode}" == "ordered" ]] && ordered_flag=1 - - ( exec {fd_trap_ack_w}>&-; ring_numa_ingest ${fd0} ${fd_write} $FORKRUN_NUM_NODES $ordered_flag ) & - - for (( i=0; i&-; ring_indexer_numa ${fd_scan} $i ) & - done - - for (( i=0; i&- {fd_trap_ack_w}>&- - ring_numa_scanner ${fd_scan} $i $fd_spawn_w $FORKRUN_NUM_NODES - ) & - SCANNER_P[$i]=$! - exec {fd_scan_death_w[$i]}>&- - done - - else - # LEGACY FLAT PIPELINE - ( exec {fd_trap_ack_w}>&-; ring_copy ${fd_write} ${fd0}; ring_signal ) & - ring_pipe fd_scan_death_r[0] fd_scan_death_w[0] - ( - exec {fd_spawn_r}<&- {fd_trap_ack_w}>&- - ring_scanner ${fd_scan} ${fd_spawn_w} - ) & - SCANNER_P[0]=$! - exec {fd_scan_death_w[0]}>&- - fi - - exec {fd_spawn_w}>&- - - ( - exec {fd_fallow_w}>&- {fd_trap_ack_w}>&- - fallow_args=( "${fd_fallow_r}" "${fd_write}" ) - if (( FORKRUN_NUM_NODES > 1 )); then - ring_fallow_phys "${fallow_args[@]}" - else - ring_fallow "${fallow_args[@]}" - fi - ) & - exec {fd_fallow_r}<&- - - # --- 4. RING ORDER --- - [[ "${order_mode}" == "realtime" ]] || { - ring_pipe fd_order_r fd_order_w - ( - exec {fd_order_w}>&- {fd_trap_ack_w}>&- - - order_args=( "${fd_order_r}" 'memfd' ) - [[ "${order_mode}" == "buffered" ]] && order_args+=( "unordered" ) - (( FORKRUN_NUM_NODES > 1 )) && order_args+=( "numa" ) - - ring_order "${order_args[@]}" >&${fd1} - ) & - exec {fd_order_r}<&- - export FD_ORDER_PIPE=$fd_order_w - } - - # --- WORKER DEFINITION --- - printf -v cmdline_str '%q ' "$@" - - # 1. Replace {ID} with the Worker ID, NUMA Node ID, and Worker Batch Num - if ${insert_id_flag:-false}; then - cmdline_str="${cmdline_str//\\\{ID\\\}/\{\${RING_NODE_ID:+\$\{RING_NODE_ID\}.\}\$\{ID\}.\$\{W_BATCH\}\}}" - fi - - ${dry_run_flag:-false} && printf -v cmdline_str 'echo %q' "${cmdline_str}" - - ring_ack_str="ring_ack $fd_fallow_w" - - # Determine if the target command is safe for direct posix_spawn - local cmd_type - if ${prefer_external_flag:-false}; then - cmd_type=$(type -Pt "$1" 2>/dev/null) - else - cmd_type=$(type -t "$1" 2>/dev/null) - fi - local use_ultra_fast_path=false - - # Only use the fast path if it's an external file, safe mode, and no {} insertions - if [[ "$cmd_type" == "file" ]] && ! ${unsafe_flag:-false} && ! ${insert_args_flag:-false}; then - # Resolve absolute path (e.g., "grep" -> "/usr/bin/grep") - local cmd_path=$(type -P "$1" 2>/dev/null) - - if [[ -n "$cmd_path" ]]; then - # Check if it's a compiled binary or has a shebang - if ring_is_spawnable "$cmd_path"; then - use_ultra_fast_path=true - fi - fi - fi - - if [[ -n "${c_plugin_arg:-}" ]]; then - # Ensure the user actually passed a colon! - if [[ "$c_plugin_arg" != *:* ]]; then - echo "forkrun [FATAL]: -C requires format 'path/to/plugin.so:function_name'" >&2 - return 1 - fi - - # C PLUGIN PAYLOAD (ULTRA-FASTEST PATH) - local plugin_so="${c_plugin_arg%:*}" - local plugin_fn="${c_plugin_arg#*:}" - - type -P realpath &>/dev/null && plugin_so="$(realpath "$plugin_so")" - - # --- JIT C-COMPILER LOGIC (With Fileless Execution) --- - local plugin_c="${plugin_so%.so}.c" - - # Recompile if .so is missing, or if .c is newer than .so - if [[ -f "$plugin_c" && ( ! -f "$plugin_so" || "$plugin_c" -nt "$plugin_so" ) ]]; then - if type -P gcc >/dev/null; then - local target_so="$plugin_so" - local use_memfd=false - - # Check if we have write access to the directory - if [[ ! -w "${plugin_so%/*}/" ]]; then - use_memfd=true - fi - - if $use_memfd; then - ${verbose_flag} && echo "forkrun [INFO]: Read-only filesystem detected. Compiling $plugin_c to memfd..." >&2 - ring_memfd_create plugin_memfd - target_so="/proc/self/fd/$plugin_memfd" - else - ${verbose_flag} && echo "forkrun [INFO]: Auto-compiling $plugin_c -> $plugin_so" >&2 - fi - - # Compile directly to the target (Disk or RAM) - gcc -O3 -shared -fPIC -march=native "$plugin_c" -o "$target_so" || { - echo "forkrun [FATAL]: Auto-compilation of $plugin_c failed." >&2 - return 1 - } - - if $use_memfd; then - # Seal the memfd to prevent tampering, and override the plugin_so path - ring_seal "$plugin_memfd" - plugin_so="$target_so" - fi - else - echo "forkrun [FATAL]: 'gcc' is not installed to compile $plugin_c." >&2 - return 1 - fi - fi - - # Sanity check: Ensure we actually have a target to execute before spawning workers - if [[ ! -f "$plugin_so" ]]; then - echo "forkrun [FATAL]: Plugin '$plugin_so' not found or could not be compiled." >&2 - return 1 - fi - - if [[ ${delimiter_val} ]]; then - printf -v delimiter_str '%q' "${delimiter_val}" - else - delimiter_str="''" - fi - - pCode=' - ring_call $fd_read $REPLY '"${delimiter_str} ${plugin_so@Q} ${plugin_fn@Q}" - - elif ${stdin_flag}; then - # STDIN PAYLOAD - if $use_ultra_fast_path; then - # ALL-IN-C ZERO-COPY PIPELINE - pCode='ring_exec_splice $fd_read $REPLY '"$cmdline_str" - else - # STANDARD BASH PIPE PIPELINE - : "${RING_BYTES_MAX:=1000000000}" "${RING_PIPE_CAPACITY:=65536}" - - local exec_cmd_str="$cmdline_str" - pCode=' - pipe_open_flag=0 - if (( REPLY <= RING_PIPE_CAPACITY - 4096 )); then - ring_pipe pr pw - pipe_open_flag=1 - else - RING_PIPE_CAPACITY_CUR=0 - fi - - # opportunistically probe the kernels granted capacity - if (( pipe_open_flag && REPLY <= RING_PIPE_CAPACITY_CUR - 4096 )); then - # FAST PATH (Synchronous) - # Note: ring_splice "close" closes $pw internally. We only close $pr. - ring_splice $fd_read $pw "-" $REPLY "close" 2>/dev/null || exec {pw}>&- - '"$exec_cmd_str"' <&$pr' - if ${retry_nonzero_exit_flag}; then - pCode+=' || exit $?' - elif ${is_func_flag}; then - pCode+=' - ret=$? - (( ret == 137 || ret == 139 || ret == 200 )) && exit $ret' - fi - pCode+=' - exec {pr}<&- - else - # SLOW PATH (Asynchronous) - # Close both FDs so they do not leak into the pipeline - (( pipe_open_flag )) && exec {pr}<&- {pw}>&- - ( ring_splice $fd_read 1 "-" $REPLY "close" ) | ( '"$exec_cmd_str"' )' - if ${retry_nonzero_exit_flag}; then - pCode+=' || exit $?' - elif ${is_func_flag}; then - pCode+=' - ret=$? - (( ret == 137 || ret == 139 || ret == 200 )) && exit $ret' - fi - pCode+=' - fi' - fi - - elif ${byte_mode_flag}; then - # BYTE MODE WITHOUT PASS-BY-STDIN - # BYTE ARGS PAYLOAD - array_var='"${A}"' - if ${insert_args_flag:-false}; then - cmdline_str="${cmdline_str//\\\{\\\}/$array_var}" - else - cmdline_str+=" $array_var" - fi - - if $use_ultra_fast_path; then - # Length 0 bypasses do_tokenize and acts as pure vfork wrapper - pCode='ring_exec 0 0 '\'''\'' '"$cmdline_str" - else - pCode=' - ring_lseek $fd_read - SEEK_SET _dummy - read -r -u $fd_read -N $REPLY A - '"$cmdline_str" - fi - - else - # LINE ARGS PAYLOAD (Default) - - if $use_ultra_fast_path; then - # ULTRA-FAST PATH: Bypass Bash AST entirely! - if [[ ${delimiter_val} ]]; then - printf -v delimiter_str '%q' "${delimiter_val}" - else - delimiter_str="''" - fi - - # $cmdline_str already contains the quoted command and fixed args - pCode=' - ring_exec $fd_read $REPLY '"${delimiter_str}"' '"$cmdline_str" - else - # STANDARD FAST PATH: Mapfile replacement for Shell Functions & Builtins - array_var='"${A[@]}"' - ${unsafe_flag} && array_var='${A[*]}' - - if ${insert_args_flag:-false}; then - cmdline_str="${cmdline_str//\\\{\\\}/$array_var}" - else - cmdline_str+=" $array_var" - fi - - if ${unsafe_flag}; then - cmdline_str="IFS=' ' ${cmdline_str}" - fi - - if [[ ${delimiter_val} ]]; then - printf -v delimiter_str '%q' "${delimiter_val}" - else - delimiter_str="''" - fi - - pCode=' - ring_map $fd_read $REPLY A '"${delimiter_str}"' - '"$cmdline_str" - fi - fi - - [[ "${order_mode}" == "realtime" ]] || { - pCode+=' >&${fd_out[$RING_WID]}' - ring_ack_str+=' ${fd_out[$RING_WID]}' - } - - ${stdin_flag} || { - if ${retry_nonzero_exit_flag}; then - pCode+=' || exit $?' - elif ${is_func_flag}; then - pCode+=' - ret=$? - (( ret == 137 || ret == 139 || ret == 200 )) && exit $ret' - fi - } - - worker_func_src='spawn_worker() { -( - LC_ALL=C - set +m - export RING_NODE_ID="$2" - export RING_WID="$3" - export FD_TRAP_ACK_W="$4" - - _ring_registered=false - - trap '"'"' - status=$? - ${_ring_registered} && { ring_worker dec; ring_cleanup_waiter; } - - if (( status != 0 && ${FRUN_CLAIM_BYTES:-0} > 0 )); then - (( RING_NUM_KILLS++ ))' - [[ "$order_mode" != "realtime" ]] && worker_func_src+=' - [[ -n "${fd_out[$RING_WID]:-}" ]] && ring_revert_output "${fd_out[$RING_WID]}" - ' - worker_func_src+=' - ring_escrow_put "$RING_NODE_ID" "-" "-" "$RING_NUM_KILLS" - fi - - # Notify parent that the trap successfully fired - if (( status != 0 )); then - echo "$RING_WID" >&"${FD_TRAP_ACK_W}" 2>/dev/null - fi - exit $status - '"'"' EXIT - - trap '"'"'ring_abort - kill -INT '"${BASHPID}'"' INT - - { - ID="$1" # ID is passed purely for user payload compatibility/insertion - RING_NUM_KILLS=0 - RING_POISONED=0 - FRUN_CLAIM_BYTES=0 - REPLY=0 - ' - [[ "$order_mode" != "realtime" ]] && worker_func_src+=' - # Initialize the output tracking for this specific worker slot - [[ -n "${fd_out[$RING_WID]:-}" ]] && ring_ack_init "${fd_out[$RING_WID]}" - ' - ${insert_id_flag:-false} && worker_func_src+='W_BATCH=0 - ' - worker_func_src+='shift 4 - ring_worker inc - _ring_registered=true - while ring_claim FRUN_CLAIM_BYTES; do - if [[ "${RING_POISONED}" == "1" ]]; then - echo "forkrun [WARN]: Skipping poisoned batch $RING_BATCH_IDX (killed ${RING_NUM_KILLS} times)." >&2 - echo "P:${RING_BATCH_IDX}:${RING_NUM_KILLS}" >&"${FD_TRAP_ACK_W}" 2>/dev/null - else - REPLY=$FRUN_CLAIM_BYTES - if [[ "$REPLY" != "0" ]]; then - ' - ${insert_id_flag:-false} && worker_func_src+='((W_BATCH++)) - ' - worker_func_src+="${pCode}"' - fi - fi - '"${ring_ack_str}"' || break - - # Reset variables natively in Bash so C does not have to allocate them - RING_POISONED=0 - RING_NUM_KILLS=0 - FRUN_CLAIM_BYTES=0 - REPLY=0 - done - } {fd_read}<"/proc/self/fd/'"${ingress_memfd}"'" 1>&${fd1} 2>&${fd2} -) & -P[$3]=$! -W_NODE[$3]=$2 -}' - - eval "${worker_func_src}" - - # --- SPAWN LOOP REACTOR --- - nWorkers=0 - local -a node_workers W_NODE fd_worker_r fd_worker_w P wID_free - - local -A trap_ack_pending - local _poll_timer_cmd=0 - local _timer_armed=false - local _ret_val=0 - local -a POISONED_BATCHES=() - - for ((i=0; i 0 )); then - echo "forkrun [FATAL]: Worker(s) [ ${!trap_ack_pending[@]} ] exited non-zero and EXIT trap did not confirm recovery within 3s grace period. Aborting." >&2 - ring_abort - NORMAL_EXIT_FLAG=false - _ret_val=2 - fi - ;; - TRAP_ACK) - # NEW: Catch Poisoned Batch Signals - if [[ "$POLL_ARG1" == P:* ]]; then - local p_data="${POLL_ARG1#P:}" - POISONED_BATCHES+=("Index ${p_data%:*} (failed ${p_data##*:} times)") - continue - fi - - wID=$POLL_ARG1 - (( trap_ack_pending[$wID]-- )) - - # If it balanced out to 0 (DEATH arrived first), clean it up - if (( trap_ack_pending[$wID] == 0 )); then - unset 'trap_ack_pending[$wID]' - fi - - if (( ${#trap_ack_pending[@]} == 0 )); then - _poll_timer_cmd=-1 # Cancel timer cleanly - _timer_armed=false - fi - ;; - SPAWN) - spawn_count=$POLL_ARG1 - node_idx=$POLL_ARG2 - - target=$(( node_workers[node_idx] + spawn_count )) - (( target > node_worker_max )) && target=$node_worker_max - - for (( ; node_workers[node_idx] < target; node_workers[node_idx]++ )); do - for wID in "${!wID_free[@]}"; do break; done - unset 'wID_free[$wID]' - - ring_pipe fd_worker_r[$wID] fd_worker_w[$wID] - spawn_worker "$wID" "$node_idx" "$wID" "${fd_trap_ack_w}" - exec {fd_worker_w[$wID]}>&- - ((nWorkers++)) - done - ;; - WORKER_DEATH) - wID=$POLL_ARG1 - wait "${P[$wID]}" 2>/dev/null - status=$? - - exec {fd_worker_r[$wID]}<&- - unset 'fd_worker_r[$wID]' 'fd_worker_w[$wID]' 'P[$wID]' - - node_idx=${W_NODE[$wID]:-0} - unset 'W_NODE[$wID]' - - (( node_workers[node_idx]-- )) - - if (( status != 0 )); then - (( trap_ack_pending[$wID]++ )) - - if (( trap_ack_pending[$wID] == 0 )); then - # TRAP_ACK already arrived! Clean up safely. - unset 'trap_ack_pending[$wID]' - elif (( trap_ack_pending[$wID] > 0 )); then - # Death arrived before TRAP_ACK. Arm the 3-second deadline. - if ! $_timer_armed; then - _poll_timer_cmd=3000 - _timer_armed=true - echo "forkrun [WARN]: Worker $wID (node ${node_idx}) exited with status $status. Waiting up to 3s for EXIT trap confirmation." >&2 - fi - fi - - # Unconditionally respawn replacement worker - ring_pipe fd_worker_r[$wID] fd_worker_w[$wID] - spawn_worker "$wID" "$node_idx" "$wID" "${fd_trap_ack_w}" - exec {fd_worker_w[$wID]}>&- - ((nWorkers++)) - (( node_workers[node_idx]++ )) - else - wID_free[$wID]='' - fi - ;; - SCAN_DEATH) - sID=$POLL_ARG1 - wait "${SCANNER_P[$sID]}" 2>/dev/null - status=$? - - if (( status != 0 )); then - echo "forkrun [FATAL]: Scanner $sID exited with error status $status. Aborting to prevent data loss." >&2 - ring_abort - NORMAL_EXIT_FLAG=false - _ret_val=1 - fi - - exec {fd_scan_death_r[$sID]}<&- - unset 'fd_scan_death_r[$sID]' 'SCANNER_P[$sID]' - ;; - EOF) - fd_spawn_arg="-1" - ;; - esac - done - : "${NORMAL_EXIT_FLAG:=true}" - - ${verbose_flag} && printf '\nSPAWNED %s workers\n' "${nWorkers}" >&2 - - # --- SHUTDOWN --- - exec {fd_spawn_r}<&- {fd_fallow_w}>&- {fd_trap_ack_r}<&- {fd_trap_ack_w}>&- - [[ "${order_mode}" == "realtime" ]] || exec {fd_order_w}>&- - - wait - - { ${stats_flag} || ${verbose_flag}; } && (( FORKRUN_NUM_NODES > 1 )) && ring_numa_stats - - if (( ${#POISONED_BATCHES[@]} > 0 )); then - echo -e "\n=================================================================" >&2 - echo "forkrun [ERROR]: POISONED BATCH SUMMARY" >&2 - echo "=================================================================" >&2 - echo "The pipeline completed, but ${#POISONED_BATCHES[@]} batch(es) failed repeatedly" >&2 - echo "and were permanently skipped:" >&2 - for b in "${POISONED_BATCHES[@]}"; do - echo " - Batch $b" >&2 - done - echo "=================================================================" >&2 - - # If we were going to exit 0, change it to exit 3 to signal data loss - (( _ret_val == 0 )) && _ret_val=3 - fi - - exec {fd_write}>&- {fd_scan}>&- {ingress_memfd}>&- - - } {fd_write}>"/proc/${BASHPID}/fd/${ingress_memfd}" {fd_scan}<"/proc/${BASHPID}/fd/${ingress_memfd}" {fd0}<&0 {fd1}>&1 {fd2}>&2 - return $_ret_val - ) {fd00}<&0 {fd11}>&1 {fd22}>&2 -} - -# ============================================================================== -# BASH AUTO-COMPLETION FOR FRUN -# ============================================================================== -_frun_complete() { - local cur prev opts - COMPREPLY=() - cur="${COMP_WORDS[COMP_CWORD]}" - prev="${COMP_WORDS[COMP_CWORD-1]}" - - # V3 Supported Flags - opts="-k --keep-order --ordered -u --unbuffered --realtime --buffered --atomic \ - -U --unsafe +U --safe -s --stdin +s --no-stdin -v --verbose +v --no-verbose \ - -z --null -N --dry-run -i --insert -I --insert-id -n --limit -L --exact-lines \ - -E --retry-nonzero-exit +E --no-retry-nonzero-exit \ - -l --lines --batchsize -b --bytes -j -P --workers -t --timeout --nodes --numa \ - -o --order -d --delim --delimiter -h --help --usage" - - # If the user is currently typing a flag - if [[ ${cur} == -* ]] ; then - COMPREPLY=( $(compgen -W "${opts}" -- "${cur}") ) - return 0 - fi - - # If the user is typing the command to parallelize - if [[ ${prev} == frun || ${prev} == -* ]]; then - COMPREPLY=( $(compgen -c -- "${cur}") ) - return 0 - fi -} -complete -F _frun_complete frun - - -# ============================================================================== -# AUTO-BOOTSTRAP FOR FRUN LOADABLES -# ============================================================================== -_forkrun_bootstrap_setup() { -## HELPER FUNCTION TO LOAD THE RING LOADABLES USED BY FORKRUN - -# Define helper functions used by _forkrun_bootstrap_setup -_forkrun_get_arch() { - - local ARCH0="$1" - - : "${ARCH0:=$(uname -m)}" - - case "$ARCH0" in - x86_64[-_]v[2-4]) - ARCH="${ARCH0//_v/-v}" - ;; - x86_64) - if grep -qE '( avx512[cdbwdqvlf].*){5}' &2 - return 1 - ;; - esac - return 0 -} - - - -_forkrun_base64_to_file() { - local b b0 b1 k kk fd0 fd1 out0 out outC outN outF outB outFile nnSum nnSum_md5 nnSum_sha256 noVerifyFlag doneFlag IFS extglobState legacyFlag noCompressFlag - local -a compressV compressI outA - #local LC_ALL=C - local -I extglobState - - { - - # parse options - [[ "${extglobState}" == '-'[su] ]] || { - if shopt extglob &>/dev/null; then - extglobState='-s' - else - extglobState='-u' - fi - } - shopt -s extglob - - if [[ "${1}" == '--force' ]]; then - noVerifyFlag=true - shift 1 - else - noVerifyFlag=false - fi - - [[ -t 0 ]] && { - printf '\nERROR: pass the base64-encoded sequence on stdin. ABORTING.\n' >&2 - return 1 - } - - # determine if we are outputting to stout or to a file - exec {fd0}<&0 - if (( $# > 0 )); then - [[ -f "$1" ]] && \rm -f "$1" &>/dev/null - outFile="$1" - : >"${outFile}" - else - outFile=/proc/${BASHPID}/fd/1 - fi - exec {fd1}>"${outFile}" - - # read dataheader and data - read -r -d $'\034' -u "${fd0}" out0 - read -r -d $'\035' -u "${fd0}" out - if [[ -z ${out} ]]; then - # first char of data section was $'\035' --> using standard base64(+gzip) - legacyFlag=false - read -r -d $'\036' -u "${fd0}" out - if [[ -z ${out} ]]; then - # second char of data section was $'\036' --> payload was gzip compressed - read -r -d $'' -u "${fd0}" out - noCompressFlag=false - else - noCompressFlag=true - fi - else - legacyFlag=true - fi - - exec {fd0}>&- - - if [[ -z ${out} ]]; then - # if data header is missing then the base64 may have been made with standard base64 decoding. attempt to work with this. - out="${out0}" - grep -F '+' <<<"${out}" | grep -qF '/' && { base64 -d <<<"${out}" >&$fd1; return; } - noVerifyFlag=true - outN=0 - outF='' - nnSum=0 - else - # parse the data header to get various parameters - { - read -r outN outB - read -r nnSum_md5 - read -r nnSum_sha256 - ${legacyFlag} && mapfile -t compressV - - } <<<"${out0}" - - # determine checksum to use. prefer sha256 - if type -p sha256sum &>/dev/null; then - nnSum="${nnSum_sha256}" - elif type -p md5sum &>/dev/null; then - nnSum="${nnSum_md5}" - else - noVerifyFlag=true - fi - - - # restore full base64 sequence - ${legacyFlag} && (( ${#compressV[@]} > 0 )) && { - compressI=('~' '`' '!' '#' '$' '%' '^' '&' '*' '(' ')' '-' '+' '=' '{' '[' '}' ']' ':' ';' '<' ',' '>' '.' '?' '/' '|') - - for (( kk=${#compressV[@]}-1; kk>=0; kk-- )); do - out="${out//"${compressI[$kk]}"/"${compressV[$kk]}"}" - done - } - fi - - if ${legacyFlag}; then - - # recreate binary from base64 sequence - # this generates outF which is a string that contains the hex values formatted like: \x00\xFF\x9A\x...' - # printf '%b' then will write out the binary data using that string - while read -r -N 4 b0; do - b0="${b0%%*([^0-9a-zA-Z@_])$'\n'}" - - [[ ${b0} ]] || break - (( b1 = 64#0${b0})) - - printf -v b '%06X' "${b1}" # always generate full 6 hex digits first - - (( outN < 6 )) && b="${b:0:$outN}" # then slice only if it's the final group - - (( outN = outN - ${#b} )) # subtract actual hex digits used - printf -v outC '\\x%s' ${b:0:2} ${b:2:2} ${b:4:2} - printf -v outC '%s' "${outC%%*(\\x)}" - outF+="${outC}" - - ((outN <= 0 )) && break - done <<<"${out}" - - printf '%b' "${outF}" >&"${fd1}" - - elif ${noCompressFlag}; then - # using standard base64, no compression - base64 -d <<<"${out}" >&"${fd1}" - - else - # using standard base64 + gzip compression - base64 -d <<<"${out}" | gzip -d -c >&"${fd1}" - fi - - exec {fd1}>&- - - # verify output file and make it executable - if [[ ${outFile} ]] && [[ -f "${outFile}" ]]; then - chmod +x "${outFile}" - (( outB > 0 )) && type -p truncate &>/dev/null && truncate --size="${outB}" "${outFile}" - ${noVerifyFlag} || [[ "${nnSum}" == '0' ]] || { nnSumF="$("${nnSum%%\:*}" "${outFile}")"; nnSumF="${nnSumF%% *}"; grep -qF "${nnSum#*\:}" <<<"${nnSumF}" || { printf '\n\nWARNING FOR EXTRACTED LOADABLE:\n"%s"\n\nCHECKSUM DOES NOT MATCH EXPECTED VALUE!!!\nDO NOT CONTINUE UNLESS THIS WAS EXPECTED!!!\n\nEXPECTED: %s\nGOT: %s\n\nTHIS CODE WILL NOW REMOVE THE EXTRACTED .SO FILE AND ABORT\nTO FORCE KEEPING THE [POTENTIALLY CORRUPT] .SO FILE, RE-RUN THIS CODE WITH THE "--force" FLAG' "${outFile:-\(STDOUT\)}" "${nnSum}" "${nnSumF}" >&2; ( read -r -u ${fd_sleep} -t 2 ) {fd_sleep}<><(:); \rm -f "${outFile}"; return 1; }; }; - elif ! { ${noVerifyFlag} || [[ "${nnSum}" == '0' ]] || ! ${legacyFlag}; }; then - nnSumF="$("${nnSum%%\:*}" <(printf '%b' "${outF}"))"; nnSumF="${nnSumF%% *}"; grep -qF "${nnSum#*\:}" <<<"${nnSumF}" || { printf '\n\nWARNING FOR EXTRACTED LOADABLE:\n"%s"\n\nCHECKSUM DOES NOT MATCH EXPECTED VALUE!!!\nDO NOT CONTINUE UNLESS THIS WAS EXPECTED!!!\n\nEXPECTED: %s\nGOT: %s\n\nTHIS CODE WILL NOW REMOVE THE EXTRACTED .SO FILE AND ABORT\nTO FORCE KEEPING THE [POTENTIALLY CORRUPT] .SO FILE, RE-RUN THIS CODE WITH THE "--force" FLAG' "${outFile:-\(STDOUT\)}" "${nnSum}" "${nnSumF}" >&2; ( read -r -u ${fd_sleep} -t 2 ) {fd_sleep}<><(:); \rm -f "${outFile}"; return 1; }; - fi - - } {fd1}>&1 - - { (( ${#FUNCNAME[@]} > 1 )) && [[ "${FUNCNAME[1]}" == '_forkrun_bootstrap_setup' ]]; } || shopt ${extglobState} extglob -} - - local tmp_so dir rf bootstrap_flag need_memfd_create_flag need_memfd_b64_flag need_b64_flag have_memfd_loadables_flag force_flag fast_flag - local -a candidates - - need_memfd_create_flag=false - need_memfd_b64_flag=false - need_b64_flag=false - have_memfd_loadables_flag=false - force_flag=false - fast_flag=false - bootstrap_flag=false - - # check for -f|--force as input arg - while true; do - case "$1" in - --fast) fast_flag=true; shift 1 ;; - -f|--force) force_flag=true; shift 1 ;; - *) break ;; - esac - done - - [[ $FORKRUN_MEMFD_LOADABLES ]] && (( FORKRUN_MEMFD_LOADABLES > 2 )) && [[ -f /proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES} ]] && have_memfd_loadables_flag=true - - # fast "is everything already set up" check for runtime checks - ${fast_flag} && { - enable ring_list || { - ${have_memfd_loadables_flag} && enable -f /proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES} ring_list - } - if ring_list 'ring_funcs' 2>/dev/null && (( ${#ring_funcs[@]} > 0 )); then - for rf in "${ring_funcs[@]}"; do - enable "$rf" 2>/dev/null || { - fast_flag=false - break - } - done - else - fast_flag=false - fi - } - ${fast_flag} && return 0 - - # check for existing b64 array - (( ${#b64[@]} > 0 )) || need_b64_flag=true - - # check for existing memfd holding b64 - { [[ $FORKRUN_MEMFD_LOADABLES_BASE64 ]] && (( FORKRUN_MEMFD_LOADABLES_BASE64 > 2 )) && [[ -f "/proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES_BASE64}" ]]; } || need_memfd_b64_flag=true - - # if we dont have the b64 array and there isnt already a memfd holding it (to recover it from) abort - ${need_b64_flag} && ${need_memfd_b64_flag} && { - printf '\n\nERROR: There is no b64 array variable to generate the .so from and no memfd to recover the b64 array from. ABORTING!\nNOTE: to re-load the b64 array and setup the loadables again, run ". %s" again.\n\n' "${BASH_SOURCE[0]}" >&2 - return 1 - } - - # check for the memfd_create loadable - enable | sed -zE 's/\n/ /g' | grep -qE '(ring_((memfd_create)|(seal)|(list)) .*){3}' || need_memfd_create_flag=true - - # set ARCH - _forkrun_get_arch "$1" - - # if we need the b64 get it from the memfd - ${need_b64_flag} && { - . "/proc/${BASHPID}/fd/${FORKRUN_MEMFD_LOADABLES_BASE64}" - (( ${#b64[@]} == 0 )) && { - printf '\n\nERROR: ring_memfd_create is not loaded and there is no b64 array variable to generate the .so from. ABORTING!\nNOTE: to re-load the b64 array and setup the loadables again, run ". %s" again.\n\n' "${BASH_SOURCE[0]}" >&2 - return 1 - } - need_b64_flag=false - } - - # if ring_memfd_create isnt loaded then bootstrap it by briefly creating the .so in in a tmpfile and loading it - ${need_memfd_create_flag} && { - bootstrap_flag=true - - # Define candidates in order of preference - candidates=( - "${FORKRUN_TMPDIR:-}" # user override via env var - "${XDG_RUNTIME_DIR:-}" # Best: Standard, private tmpfs - "/run/user/${EUID}" # Fallback XDG - "/dev/shm" # Standard shared memory - "/run/shm" # Legacy shared memory - "${TMPDIR:-}" # Standard env var - "/tmp" # Universal fallback - "${HOME}/.cache" # User disk fallback - "$PWD" # Last resort - "python" # Fileless fallback via python - "perl" # Fileless fallback via perl - ) - - local py_script='import os,sys,time; fd=-1 -try: fd=os.memfd_create("b",0) -except: - try: import ctypes; fd=ctypes.CDLL(None).memfd_create(b"b",0) - except: sys.exit(1) -sys.stdout.write(str(os.getpid())+" "+str(fd)+"\n"); sys.stdout.flush() -while True: time.sleep(60)' - - local pl_script='my $a=$ARGV[0]; my $s=($a=~/^x86_64/)?319:($a eq "aarch64"||$a eq "riscv64")?279:($a=~/^ppc64/)?360:($a eq "s390x")?356:0; exit 1 unless $s; my $fd=syscall($s,"b",0); exit 1 if $fd<0; print "$$ $fd\n"; $|=1; while(1){sleep 60;}' - - # try various places to make the tmp .so file to bootstrap - for dir in "${candidates[@]}"; do - local helper_fd="" helper_pid="" helper_out_fd="" - - if [[ "$dir" == "python" ]]; then - if type -P python3 >/dev/null 2>&1; then - exec {helper_fd}< <(python3 -c "$py_script" 2>/dev/null) - elif type -P python >/dev/null 2>&1; then - exec {helper_fd}< <(python -c "$py_script" 2>/dev/null) - else - continue - fi - read helper_pid helper_out_fd <&$helper_fd - if [[ -n "$helper_pid" && -n "$helper_out_fd" ]]; then - tmp_so="/proc/$helper_pid/fd/$helper_out_fd" - else - [[ -n "$helper_fd" ]] && exec {helper_fd}<&- - continue - fi - elif [[ "$dir" == "perl" ]]; then - if type -P perl >/dev/null 2>&1; then - exec {helper_fd}< <(perl -e "$pl_script" "$ARCH" 2>/dev/null) - read helper_pid helper_out_fd <&$helper_fd - if [[ -n "$helper_pid" && -n "$helper_out_fd" ]]; then - tmp_so="/proc/$helper_pid/fd/$helper_out_fd" - else - [[ -n "$helper_fd" ]] && exec {helper_fd}<&- - continue - fi - else - continue - fi - else - # Skip empty, non-existent, or non-writable directories - { [[ $dir ]] && [[ -d "$dir" ]] && [[ -w "$dir" ]]; } || continue - - # Generate path with high entropy (30-bit random hex) - printf -v tmp_so '%s/forkrun_boot_%s_%X%X.so' "$dir" "$BASHPID" "$RANDOM" "$RANDOM" - fi - - # Try to extract loadable - if truncate -s "${b64[$ARCH]%% *}" "${tmp_so}" 2>/dev/null && _forkrun_base64_to_file <<<"${b64[$ARCH]}" "$tmp_so" 2>/dev/null; then - chmod +x "$tmp_so" 2>/dev/null - - # CRITICAL TEST: Try to Enable loadable - # This verifies the filesystem allows execution (noexec check) - if enable -f "$tmp_so" ring_memfd_create ring_seal ring_list ring_pipe 2>/dev/null; then - # SUCCESS! The builtin is loaded. - need_memfd_create_flag=false - fi - fi - - # Clean up - if [[ -n "$helper_pid" ]]; then - kill "$helper_pid" 2>/dev/null - [[ -n "$helper_fd" ]] && exec {helper_fd}<&- - else - \rm -f "$tmp_so" 2>/dev/null - fi - - # break out of loop if we found someplace that works - ${need_memfd_create_flag} || break - done - - # If we get here and stil dont have memfd_create we failed --> couldnt find a writable location - ${need_memfd_create_flag} && { - printf '\nERROR: could not write and load bootloader for loadable in any temp directory. ABORTING!\n directories checked: %s\nPlease specify a writable directory by calling "FORKRUN_TMPDIR=/path/to/writable/dir _forkrun_bootstrap_setup"\n\n' "${candidates[*]}" >&2 - return 1 - } - } - - # if we bootstrapped or if force_flag is set, forcible re-create + seal the base64 memfd backup. if force_flag is set close the previous one - if { ${bootstrap_flag} || ${force_flag}; } && (( ${#b64[@]} > 0 )); then - - # if force_flag is set then close the old base64 memfd - ${force_flag} && ! ${need_memfd_b64_flag} && exec {FORKRUN_MEMFD_LOADABLES_BASE64}>&- - - # open a memfd, write b64 to it, and seal it - ring_memfd_create 'FORKRUN_MEMFD_LOADABLES_BASE64' - export FORKRUN_MEMFD_LOADABLES_BASE64="${FORKRUN_MEMFD_LOADABLES_BASE64}" - declare -p b64 >&${FORKRUN_MEMFD_LOADABLES_BASE64} - ring_seal "${FORKRUN_MEMFD_LOADABLES_BASE64}" - need_memfd_b64_flag=false - fi - - # open a memfd, extract loadable .so to it, and seal it - ${force_flag} && ${have_memfd_loadables_flag} && exec {FORKRUN_MEMFD_LOADABLES}>&- - unset "FORKRUN_MEMFD_LOADABLES" - ring_memfd_create 'FORKRUN_MEMFD_LOADABLES' - export FORKRUN_MEMFD_LOADABLES="${FORKRUN_MEMFD_LOADABLES}" - truncate -s "${b64[$ARCH]%% *}" "/proc/self/fd/${FORKRUN_MEMFD_LOADABLES}" - _forkrun_base64_to_file <<<"${b64[$ARCH]}" "/proc/self/fd/${FORKRUN_MEMFD_LOADABLES}" - ring_seal "${FORKRUN_MEMFD_LOADABLES}" - - # get list of loadables - ring_list 'ring_funcs' - - # unload existing ring loadables - if ${bootstrap_flag}; then - enable -d ring_memfd_create ring_seal ring_list - else - enable -d "${ring_funcs[@]}" ring_list 2>/dev/null || true - fi - - # load ring loadables exclusively from memfd - enable -f "/proc/self/fd/${FORKRUN_MEMFD_LOADABLES}" "${ring_funcs[@]}" ring_list - - # clear massive b64 array - unset "b64" - - return 0 -} - - - -_forkrun_file_to_base64() { - - # local nn kk kk0 k1 k2 out out0 outF outN v1 v2 nnSum hexProg quoteFlag noCompressFlag IFS IFS0 - local -I extglobState - - # local -a charmap compressI compressV outA nnSumA - local LC_ALL=C - - [[ "${extglobState}" == '-'[su] ]] || { - if shopt extglob &>/dev/null; then - extglobState='-s' - else - extglobState='-u' - fi - } - shopt -s extglob - # parse inputs - - local quoteFlag=false - local noCompressFlag=false - local legacyFlag=false - - while true; do - case "${1}" in - -q|--quote) - quoteFlag=true - shift 1 - ;; - -n|-nc|--no-compress|--no-compression) - noCompressFlag=true - shift 1 - ;; - -l|--legacy) - legacyFlag=true - ;; - *) break ;; - esac - done - - [[ -f "${1}" ]] || { - - printf '\nERROR: "%s" not found. ABORTING.\n' "${1}" >&2 - return 1 - } - - ${legacyFlag} && { - - # define char mapping array that convero 0-63 --> [0-9][a-z][A-Z]@_ (bash 64# chars) - charmap=($(printf '%s ' {0..9} {a..z} {A..Z} '@' '_')) - outN=0 - outA=() - - # to dump the binary as ascii hexidecimals , we need od or hexdump - if type -p od &>/dev/null; then - hexProg='od -x' - - elif type -p hexdump &>/dev/null; then - hexProg='hexdump' - else - return 1 - fi - - # map each 12-bit segment (3x ascii hex chars, each representing 4 bits of data) into 2 base64 ascii chars (each representing 6 bits of data) - while read -r -N 3 nn; do - nn="${nn%$'\n'}" - (( outN = outN + ${#nn} )) - until (( ${#nn} == 3 )); do - nn="${nn}"'0' - done - (( k1 = ( 16#${nn} >> 6 ) )); - (( k2 = ( 16#${nn} % 64 ) )); - outA+=("${charmap[$k1]}" "${charmap[$k2]}") - done < <(${hexProg} -v <"${1}" | head -n -1 | sed -E 's/^[0-9a-f]+[[:space:]]+//; s/([0-9a-f]{2})([0-9a-f]{2})/\2\1/g; s/[[:space:]]//g' | sed -zE 's/\n//g'); - - IFS= - out="${outA[*]}" - unset IFS - - } - - (( outN = ( outN >> 1 ) << 1 )) - - # get orig file size - if type -p stat &>/dev/null; then - outB="$(stat -c %s "$1")" - elif type -p wc &>/dev/null; then - outB="$(wc -c <"$1")" - else - outB=0 - fi - - # embed checksums - if type -p md5sum &>/dev/null; then - nnSum="$(md5sum "$1")" - nnSumA[0]="${nnSum%%[ \t]*}" - nnSumA[0]='md5sum:'"${nnSumA[0]}" - else - nnSumA[0]=0 - fi - if type -p sha256sum &>/dev/null; then - nnSum="$(sha256sum "$1")" - nnSumA[1]="${nnSum%%[ \t]*}" - nnSumA[1]='sha256sum:'"${nnSumA[1]}" - else - nnSumA[1]=0 - fi - - # compress base64 and assemble the header - if ${noCompressFlag} || ! ${legacyFlag}; then - printf -v out0 '%s\n' "${outN} ${outB}" "${nnSumA[@]}" - else - # initial compression run - : "${testFlag:=true}" - compressI=('~' '`' '!' '#' '$' '%' '^' '&' '*' '(' ')' '-' '+' '=' '{' '[' '}' ']' ':' ';' '<' ',' '>' '.' '?' '/' '|') - compressV=() - kk=0 - for kk0 in 7 6 5 4 3; do - mapfile -t compressV0 < <({ sed -E 's/(00+)(([^0]+0?[^0]+)*)/\1\n\2/g; s/([^0]+)/\1\n/g' <<<"${out}"; sed -E 's/^((....)*).*$/\1/; s/^(.)(.)(.)(.*)$/\1\2\3\4 \2\3\4 \3\4 \4 /; s/(....)/\1\n/g' <<<"${out}" | sed -zE 's/^(....)\n/\1\n\1\n/; s/\n(....)\n(....)\n(....)/\1\n\1\n\1\2\n\2\n\2\3\n\3\n\3/g'; X="${out:0:1}"; while read -r -N 1 x; do if [[ "$x" == "${X: -1}" ]] && (( ${#X} < 32 )); then X+="$x"; else (( ${#X} > 1 )) && echo "$X"; X="$x"; fi; done <<<"$out"; } | grep -E '..' | sort | uniq -c | sed -E 's/^[ \t]+//' | grep -vE '^1 ' | sort -nr -k1,1 | while read -r v1 v2; do (( v0 = v1 * ${#v2} - v1 - ${#v2} )); printf '%s %s %s %s\n' "$v0" "${#v2}" "$v1" "$v2"; done | grep -vE '^-' | sort -nr -k 1,1 | head -n $kk0 | sort -nr -k2,2 | sed -E 's/^([0-9]+ ){3}//') - compressV+=("${compressV0[@]}") - for (( ; kk<${#compressV[@]}; kk++)); do - out="${out//"${compressV[$kk]}"/"${compressI[$kk]}"}" - done - done - - # 2 final compression runs where we re-generate the list of possible replacements and expand it to also look for simple repeated chars (with a limit of a maximum of 32 chars) - for kk0 in 1 2; do - compressV[$kk]="$({ { sed -E 's/(00+)(([^0]+0?[^0]+)*)/\1\n\2/g; s/([^0]+)/\1\n/g' <<<"${out}"; sed -E 's/^((....)*).*$/\1/; s/^(.)(.)(.)(.*)$/\1\2\3\4 \2\3\4 \3\4 \4 /; s/(....)/\1\n/g' <<<"${out}" | sed -zE 's/^(....)\n/\1\n\1\n/; s/\n(....)\n(....)\n(....)/\1\n\1\n\1\2\n\2\n\2\3\n\3\n\3/g'; X="${out:0:1}"; while read -r -N 1 x; do if [[ "$x" == "${X: -1}" ]] && (( ${#X} < 32 )); then X+="$x"; else (( ${#X} > 1 )) && echo "$X"; X="$x"; fi; done <<<"$out"; } | grep -E '..' | sort | uniq -c | sed -E 's/^[ \t]+//'; { read -r -N 1 y; while read -r -N 1 x; do if [[ "$x" == "${y: -1}" ]]; then y+="$x"; else echo "$y"; read -r -N 1 y; fi; done; } <<<"${out}" | grep -E '..' | sort | uniq -c| sed -E 's/^[ \t]+//' | while read -r v1 v2; do if ((${#v2} > 32 )); then (( v1 = v1 * ( ${#v2} / 32 ) )); v2="${v2:0:32}"; fi; printf '%s %s\n' "$v1" "$v2"; done } | grep -vE '^1 ' | sort -nr -k1,1 | while read -r v1 v2; do (( v0 = v1 * ${#v2} - v1 - ${#v2} )); printf '%s %s %s %s\n' "$v0" "${#v2}" "$v1" "$v2"; done | grep -vE '^-' | sort -nr -k 1,1 | head -n 1 | sed -E 's/^([0-9]+ ){3}//')" - out="${out//"${compressV[$kk]}"/"${compressI[$kk]}"}" - ((kk++)) - done - - printf -v out0 '%s\n' "${outN} ${outB}" "${nnSumA[@]}" "${compressV[@]}" - fi - - ${legacyFlag} || { - # new method using standard base64 and gzip - if ${noCompressFlag}; then - out=$'\035'"$(base64 -w 0 <"${1}")" - else - out=$'\035'$'\036'"$(gzip -9 -c <"${1}" | base64 -w 0)" - fi - } - - # combine header and base64 - printf -v outF '%s'$'\034''%s' "${out0%$'\n'}" "${out}" - - # print output, optionally quoted - if ${quoteFlag}; then - printf '%s' "${outF@Q}" - else - printf '%s' "${outF}" - fi - - - { (( ${#FUNCNAME[@]} > 1 )) && [[ "${FUNCNAME[1]}" == *'frun'* ]]; } || shopt ${extglobState} extglob -} - -FORKRUN_FRUN_SRC="ulimit -n $(ulimit -Hn)"$'\n' -unset "b64" - -# <@@@@@< _BASE64_START_ >@@@@@> # -declare -A b64=([x86_64_v4]=$'0 145992\nmd5sum:64ed31e2b97c37ead57b70c5a7e07bc8\nsha256sum:92e30fad3a53b39c03a51777684490ac80500cd7fe4b44f3f18dbad568aa4fab\034\035\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' [native]=$'0 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Z?J>&_@nhLFXVxQ1ewzbSmd2~~e*lh8s44&e From ed0c6782d2f79a15098bd049ce0280374fa436d6 Mon Sep 17 00:00:00 2001 From: jkool702 <107448833+jkool702@users.noreply.github.com> Date: Thu, 21 May 2026 21:07:02 +0000 Subject: [PATCH 05/10] build: update embedded ring loadables --- frun.bash | 2 +- .../forkrun-libs/forkrun_ring.aarch64.so | Bin 137416 -> 137416 bytes .../forkrun-libs/forkrun_ring.ppc64le.so | Bin 202656 -> 202656 bytes .../forkrun-libs/forkrun_ring.riscv64.so | Bin 104032 -> 104032 bytes .../forkrun-libs/forkrun_ring.s390x.so | Bin 140840 -> 140840 bytes .../forkrun-libs/forkrun_ring.x86-64-v2.so | Bin 142152 -> 142152 bytes .../forkrun-libs/forkrun_ring.x86-64-v3.so | Bin 150344 -> 150344 bytes .../forkrun-libs/forkrun_ring.x86-64-v4.so | Bin 150344 -> 150344 bytes 8 files changed, 1 insertion(+), 1 deletion(-) mode change 100755 => 100644 frun.bash diff --git a/frun.bash b/frun.bash old mode 100755 new mode 100644 index cca6637f..3626bca0 --- a/frun.bash +++ b/frun.bash @@ -1739,6 +1739,6 @@ unset "b64" # <@@@@@< _BASE64_START_ >@@@@@> # -declare -A b64=([aarch64]=$'0 137416\nmd5sum:08465cfcff2e7fd5c20162fb1e165e5b\nsha256sum:5d5c00624112f680f7ff66a99372f2e489dbb4f7de3a74d787caa57c54c3da68\034\035\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' 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' [riscv64]=$'0 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' 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' 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' [s390x]=$'0 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' ) +declare -A b64=([aarch64]=$'0 137416\nmd5sum:734afb630750d635371032000969520c\nsha256sum:4bfc1b86dcd12381b31f52680c34aaac00a294fcc3912c081ce2b6bb79f7f51a\034\035\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' 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Jtw/iO+Ced/WYnfjPMfcfwMsCB+K85/xDfj/Ed8C85/xLfi/Ed8O85/xHfg/Ed8J85/xG/D+Y/47Tj/EXfh/Ef8Tpz/iH8R5z/iu3D+I74b5z/iX8L5j/genP+IN+P8R/zLOP8Rv0v1vG6aiPb0nHyq/N60VJG5jTzmebXcsd6zeZP9qTJzysJMEw9MLZ8ofoybKStw1Wtr2IWmV6emtnOdQpQtt3ObwlPl5pTEZC2h3zeLvmi3HJ69Pdk9e7vHoN1l0N5v1L9Bu8NA32FwfbNB+5iBftTg+iGD+OcN2q0G+lmD9hEDfcngeqvB+JMG+naD620G/Q8Y6A8b6GcNrvcY9C8Z6FsM9F0G+nkD/ZyBfq2Bvs3g+kEjfYN2p4H/AYPrmUF7waA9YNB/waDdbBC/jEH/zQb6IwbtEwb64wbXjxrVZ6P702j+DfQzRvefQXufQfuA0fgN/M8ZzG+/UX03aHca1Sej+mA0/0b3j8H4Bo3qyyztjJUXzOzwSb6CbEgu8aQWfy3E1xY9O5Pl5SmxJjHzNUnxGQk+LucaYi1iJusQvZ/i89GofhjdnwbtfUbPf4P4mg3aHUbrK6P1j9Hz2aB9wkDfalS/jZ4fBvr2w7OvX3PrNtmZ/F8ceAr377UX7l/RyGrri3kkmCXTw/OroUGcK+vc9/g6V2gKfSWnpBnr200eoe+Yod9jd0mHU4lLe1OJBb2ph0y9033V/tl9CX25v5Eb5f7G719xL2PVQmsH1hJtUmYF76e+YTHraZqa2rt+LO2z7z4rr9M/uTC1XeibmNRYHD/vh2sdUfdV6s/D+5P4Gr/ES1tx/DfK7wfjU8fPTUy9dy655GAqWfe9oj9vcn8k8TEc6L0wKfvAWF13hey7w8xy9uS5E4eSH7126LpPp9sb3prKNNkgDlz7FNc+Re5pUwY+Vsb+DjbCfPTJMRCxfraCpR65ub7RxByNAaf4ryLMxbh17HSkx6d6HA0mtkOJY/H9pm9TtxjLQibdtHFTvZexuQ1iPC8Ux7P8rIfH1ca6z9nZE+fkvnPrHOz4OdbXw1//h9dZ2Ppi3w3cbtX4yUOMXdbQwjIOE3t1ncO1LLWYHwubCvbOOmH3NveB653ieqe4zimhOXj4/cPiure5rTh/Cc5D/NwFcVHHZJPnpaqpQzjeTee04y2xbh7z3x06/rE63mZ2d/fd03M9U+/MH9V6ySm13j1ET9vP0nxR/QeIvpnoLyL6OC6nL/D+ZN/l3KiA+/8GOT+lOW1JMafDC69sEPl5YapnfXJJMOX4dq/wceI4n9tBU8YhzflWcnjhVQ1H+fGRS1nqyMpc+m/LJfExbmNlILeo0swsezrYeGVNblGurL+pZg6zhMqYpY1VpqamNjcmbdvSH5dvSy++05l+3tWSet61Ne1y+XhelTckTD1Non/Rd99DvfY+1F+v6O+22fvLmP60/pjFY3+Jlfp08bG+wkp9DjLjPkOqMVbxPrc0Ju24z/pivy6n3KeJeewOnmc/53sbvydePVOaM5ep2yHqA2MbGx4s6+H5Jt0k7nuHc0PqBG/j9qfMzLPeoZPfye116Y7/kfUe5HMtzq3sveI9uRs4Pz7JWUH48uCFHscu7kcj+OAwyEesN4foDfK6yQPUeGTzsfSRzb3pSvN8S6XnuUVKnAIX+h3SLO1O3m7TbZcsVt7uYEEeu1674kP3GbUPfBK3Y3//gY/tK+Ol+B690C3HdPuG9KPT/j6p7c95xV/tdut5xd8nNf01nxf+9nJ/fdP+vjmu9rfmvNpfMb/6c7DJM1t8U+dnj+/d52eP7/ppf4P2evDTRfzjO/v8P8htXbw2JLdvTD/Luov111p8plbzLVCMdYrfV4w/T/D1VmY6K7Gms/eCBj8/yc9PmlhdYzW/bvG2bWlx7Siva8y1McVrPn8+S41SRf1ucQ+Ie+HtC/J9IHJxYlLtn2viqrTw6cTKkwdczo3pxMr6dB7Va4nP/RCugRrPx77V6noontvqmnhwuiaK590kqlHjn6Emnv5MNfGr0zVqiNTEt1F/I6K/T2fvb9L0p/U3dchjnyA10Yz6nGTGfWYNa+KGGTWxl9dEUfeWmsTeYxdrhydO41y7KT1ehnPtdb4OOFjMtVyZyLWxder11ybP8g/l6+X8Osjza+qQsC+I/Jq4KeUp624Sa4qpKY9dqvDtcumvp+T6x/NvPmg6RX3l5xK/t8+eVu5rua66oK6+dwruI6J7dKEvqVlfQe8Y0gtdKOWveGbcd6pUz4b5M8HCc9rhrEvdMiWOPevXo3yX68XPNOvB6el6od3+6+l68TPNevHsdL04aBc+f3Kq5PNQsW4o/WvXz8nJ2evr25Oz19dXJkv1VfTfifrPT+L+tcfnMRi/w2D8Ehr/2f+S+15L6qWrsDEt8vbEymO8HqVTItcSK32pfoiPeD69erI0n2uLzyfP+iS0C3uJnwfOo5pVrtQsuV6NXSPW87feK9ZqybpsKju1rVGsx2v4/WTiXBwX3634mt1WZPXBtaw+ffC39f/H3L+HR1VdDcD4PpPbJKIMMGpUlAkgzKQjBkWdyeRyJgFNgm0HBU2tl0lBC776fqHSvifmnLkEbBOldgJoE0UaFGyg6htr7Esr2ETRBkptRLRRgSaCMpOgBgGdSULOt9be5+ScmYSI/X5//PI8eWbmXPZl7XXfa629ZEKHbYlwq01i96fXJ+IjIZ/WEpJmL6HvpVtRVzLAZwf8nk7a8iykKc8A+GcgRutFqTctIUnHlk2gtGi1LwM6viC1bIlw7R6RJJXd2wB42Skfc2B75VQ2fFr7nvw3+J1qb6Dtv1XbKb9Nf9fCbwP8xu+i0vcpjvV9kH4arYKhhp+TVrYE8N/JcL7Iyynj3SKzdxbL2I7RWoJjSSlbQiwW516ubMkE5Xm8N4Fj7YBscJ5K0B/eV8bXDON9Txn7Pugf5YPwveeAdwUcGaB/q/pxDsg3K8h5kGn1W0fw0R2EaxG4F6m67Keikc6n24HjKzewOZkMbE5HKQ8kXhyPNfRJNABjQn1AXSPkIbhOKu8QXL0ir+MPehh6ZA2G8xV49GvrR/srV+bOQz9RwLHryU1LYF0dBmr7Wu1N8N4cwtawC3HwTHceMViccv8xL5ne5nA4bpLwObRz1LVG+L6g4O8VeO1728QLkgD2gAMb6HUrxUcLzK8JxnE9tA86mTMT1mQS4JQJcAps73xsA8e4myhrZ2Jrp+kkbP0C0AbiXjK8g/g3H9oInNHWd6P6Ps/eN53Rw+vT2n8q62ofRngx/DkwXOOeqsAV549rUQtjXDXMYATjpP6Bg/Ab5wjwy1fn2DLEnoFxOGBMzh3DCtw4BW6TGNw61OvJyvX57Drq0TjuJsLoCMfAQ/9mOk8Kq3zsJwzzQJjXKr/xuRJ4rlOBm0XBJTp3wubugPskYKt4QbcOOXAtE/s6Q/KJEcdirHDwZVKtAifsI+79WlvFA2fYvAO6eQf0ehX9UPw/Ns3/UfW918U2mRvskLMGO2X3YJdcMdgtBwfD8mbqG0E6GpZJXpNMvPdzWSLqPsJlDwNfaxSZfPe6OFASPP2vieaPPhT5tiuBnoKA20151AZ+r9h/VUTVGUTRSwJuXP+lYP+aOdQdssLCR4f9suzLMZ1Yij6YMIynD8bTB+Pp6yRLRRhTH4ypD8bUh/K6NW2peDZ7iOuLt8eB57rPg0/kjxnA292KHOe7CsSb5aA7IMfzF+HI70Deb3aN/B781C/0bfGjPrTgqCYXrDCPRdEjfvOlu/zoCzF/Uu1HeDQntLdSkUMoC7B/Qmx0XOeRuquN1CeziX+xT7MP8RmOyK5G5Vq5nKjvZ4VRN0IYJMIqEU7xMPK6Ngzr8MGo4UPObIYP6vrj+qo4IHxvpyhcJmm+shmbgM/+VUyG9hA3Niv+uzh4ndwNMHvOf+ERDV4lI/A6TOHlRR56ZLUf5/DtY9fpjwouyXITwAmrhs4IWkiFQ4VpQAY+ATAFHr9+JqlYv7KHPb9ckS/YL8LvHPtlsEqNl+9kVpEDYVEF9gfCTFiYKwUBDvOBNobBNuIDtiq+pFC0cEEql7wkCDAVQdfoGaC8g3CD5QTgXHyx5Aj8xLEc9OpK0g6w3iUK13aJgmtQDAFsXz3G1p4j9wDvn5FPyNK82oDNGQi86WJ2nS/M89nicbDJSkjWIPrx8HlHYLrT/NVq0dx7WPREXxcRzsJCp7T1U5UO7xdvhvU4BfhnvuWwn+8vFIW/z/CfArp1K32q7xJSnB8IoP5yfxjbxLbu0rWzUw7wvz4WT3MtsAYw116YZx+Mqw/mEob59gEc+mCufTBXCuMA9el6HbgOCHcGc5vdSPlsZJBOBZ7R3+fI7/KYPA9Gf66jR7Q34FoY5TqDhQ/wsi56PEF/wLkuA7rX6Ak7+Ymj9DP1OZ7COgBwhjH0mb8qlF46cY+E6ykszJNaqG/TZd8BY2xNS/ejHxVha6U+QWzP4uTIsAv9poQUNC5SxshH88Q8gK+n+68A65l+9A2++m91/G0Olc9UoS/646X+HTK1vai/fDm1v3IVuPxlEOGphy9OYSz47qZzb3Lt1tkf1P+YluFHHBFuLQdd2CUZyA3OmdOGH1bn0qbzb26ZWFJ1dNb8KhwTwhz9BZd/ytpj8OYiiCOIm5WAJ0JgBsUV9CnA2GPvfqKt0fEzuEZueP7+KIXDm8kUDi8e1tmU0E+D4qdA/wyDY2njtqNqn1kR1tdSoP3iSPaJXuDNEZeRHHYhjLuGgzy2UXVUxWOnhM8LyvN8STbg9HbgEwF+prwJ1IQAhug6cb8A4U/XAd7HNXniE9VW3eUKUFiy9Vg1XONmbf/Lj7gzc9rh6vSjKq3ieGfkV1L8scH4Iv758K66XqeGdDw4nfl7W7KKgA6S7MlJQX4kbmkwK2oky8Koz55/WIVhkr3NEHCT5CYHrLVjeXJFdK6CQ8uTsyJe+I0+mHyF53mTcW2s9rUGlMdWeyvQCPC/uhkoDw24z1LinEiyrQfg/tHUtKq1SRj6yzv75dlOD2l3GHpsVWCbAD5fuXImrImJ0kaT4x3PLDGVZJlSk7NMi0kD2LizrZnQXlHUVvV8kk2aqcMffFZYeKWkPj8Tnj/O8UUmkg34t0AykVLnOyVae51yg1v43u9Fc65b8pIyaivZoW2O3OQkHquI9rX5Fu0e09PZvS0J99A+SVLu1Sbc64J7ycq9BxLu7YR7Kco9T8K9JriXqtybl3BvDdxLU+5lJtwDGgY7kt0bIvH3boZ76cq97oR7OXAvQ7m3O+GemUPdht1rTriH/qIJyr21CfcOwr3zlXuVCffa4N4Fyr3FCfe2wL2JZLaTlFhBlsG9siy4t6J2Huhovg+XLubI0uXa2iv81gFwGmZ6L9PvvY7K5KwR/SXRn4P38Z7qP/eSirj2dyfoQxXEXZcFY5t3Bvtg/tAm+ky6/ZSMeIM42+3YdyZRF9bkec4VRY4koC0zyNHE/pEeVd0Y7coRvWjGM7r9Q784LP/O1Zq20U/3NM9otPvyvxgt4rv4W7isCuYthS85pOqFD4uqDHrr3+rcmKwXgIdUUllfCnR8RYT35IndhqA7ylUMnpELlb3QQy7k4RZSWOUI1Lj65V0z9PAxf5UvocxOJ3dHsktLpAqlD1mWb0C+XUlle0YE/butaT/1d3EV0RauwtHJuWMzpx0Tsp1h/1U6/tMJsuhPXEUYbcK05IDjxMcKr4F3HvmIff8jF8RYSwdee1eZ55/gGv7mlLZgXR1LDrLvkwAu+Hvrv9R7QUc32exAsJz4gF2D8USQJ3u5zY42aIeQ3jDzOxbB9V+FcQ4LulSY+sQ/whivO6iNzfaROocrgPazIplAOziPSQfV601gY3sdO7ie9UCDjiqlX4B1H+KExaDhrKpvn4u+uvJwvG5kQvvpyBr/+dDmqyOwqQjXfaw+B/Ypl1U/VdEn5ia87wD4vwHP43hRz577L1UfTrIfAHzHsatzefV9dg/aC/rJjJUHCNLDDOeqNJvEQVtdhOJSn0XW298gb1An47JiFx5SYY8yN9e+g2t3oR4Lci1/uSLfoO1Yjoy6UL4f7/+J24zr4vR0yiLVaxRbYNuHOj1gOOAeAhlqvlT2852F4j454GZ6GtgPxUnSzGlrqkF3G3ziI1UvWC6K8DziPaxfLFnnLyDyjJVTCb3XN/3tGVXl0A5+D5CljpuV7yh/9XB55oC2tjP1NlEak8eWS5k9NCw/mydcdp9Yvm6rA+5Sn9KJWFYU5Kyj8ZA6H8Bd+L3iA41GLCCjjak9g17S4yKp7YMor9keYsARTQHeATrPhwreyUlaLMG9/1LxV6L7Kj8fgVk+9St7SftjIKMneVM2g+0VcPSnBActMKccgHN3Ss9g45dE4oHXedBHOvtyqSB1z+1e4H+NV18uIT+sBNxqvOFyWPuAq7HwcqnxJvi/Hf5/eLk0RHUusK/+pfZZHEEcRFsU2ybk349he9hOJzwbPv9w9ZyvsiVitK0Ee86Nc6L8MSXo2LWftQHv9Sl7p3VXwXsq/nHkbpAhGaIn0wf0slRoTTvsx+uoO6Ato6cfOekKa827e6pfT917+8xptqrrPY/Cs4dh/kF3dsnlknBrhpRdepfUJWN6wL8fk8meh3JIzYh+b4d+M8AutMIYQd9z6+eDz3YD3xP6tvoD1Jb0OoIKzAG2fbBWfbB+fbCWfabUsWQW0ovfoc67O6Ui2v6uNneSeYXYALYG+jb1baH92QLX0F+Fc56aEAMwav/rYsXeBDmzGWRLk+LvLDEwOeQxtA/+GMZfaeCi3Af6/ZkCycOxtdn2HrtuvtQvyvKMursALvOAl3j6/yrK5Eor6EBuxEML8Mocw+ZolUJ78B3992DPbHKgfSnMWC3mGIJRc/ZfRcK99fSi91T+85wD25kJ7cD9MPaJ7czVtwNtm7M3A+zeevrD/Ro/QH3ECvyNJ9krCYwpmQBO0TW0OIHvxnLg3/ahxh8R3hZDEGjqfhH7ISS7Psfgji3oVPy7BuBXUZvI7Agb1dnXkhoengE+lh2cDr9xLxTXXbhsGeVTOLZPFdgBHMMA2z6AK+XpOTp9ltkI2GeT4/39Yz/vBVmh2qvY7q/f1+aaCfimf159dsR/3Pc8tUEsHPKrbsfKs4xpo3z2/QfvhYx/4V4G8qxFclY00qmNYSrobi1nidcaln+Sh3wqsG6p44l3NZ62gwSAx68APRP0nYWFkiqf6v8VL5+6Ac7TCLNPEE71+zV8xPiXWQRsTrjeALZdiLjr6xVeDN+DFq5cgvfdDdTG452oE+BaB6AtpmuWNrYr7QXoM7a6fwOuLIR+ca2/r3ziHGGcfVNlFtPx+T+1uVuUuc+ctlQYa/50/+ef+pidoJsn3rxOVT7B2A8pOI9tYz+/1j2/BZ7fqZOny5YsFSrh99Fnlwrog8LnH9CvHTea3pumsPVjuuUyEdcE97pbYE1wPd2wnh++o/W5ls65uO6fyj4T25+ZUcd4fg3Pk0AethHgmhw1/BpvB7Tz539qa4u+STsJjHquH56rT3iuG/CgjSAvnCGNFe+C73fBe07d+G5OGF+ebny4/5WqxNMt57yOivfj+9sgB3g9fAy6Z69LeHY5PMtptBa8CNpPRv4OzyO94jtcwjtHQRfJ0a3XsGzIH5an5xvX2yIoO6PrjBQPm4g71nAjAXspK9ZwOydWJcAF/cHsuaz6XQpOw/fggQT/k9q+Zb0tCG1G8B3TeqNTabse2748oe1mmNfa4bFwhuFL5SSGL2iXoH2C+sOsQKWk2icqTVvXL3UYSUU94hAHOPTqP7R+mil9+8RE++3l9xL0V0MN71fpG3SUl7V1noN2UKcccuP1P3eq++zrKB83D/T4vaSw0UuyNj9YkW4XDGjXMpsIYRB5R9OnUMfEMXtgvJN0Y8T4NnUulXDv9D7t3ilu7PGf2B8//jYufvwn/jH2+GPKGmzktPHrx4tzuU4Z82cin7/mE0u+54GyigtIaRWOH/f/vSAL1fE2wXgX6MY7/yzjde8fZS/Ejdd9lvGWKuM9Hgdvxj9xrDiGR/6hyVA+M0+cR3Wt/Bjhsqjug/QM+BEc064JVkpI457uGdI+Hb1g3/9Q4LAMcBTnpI+PXPlu/Hw65fj5rNw39nyqlDbnyev4CcPx/d31jqpzeB049nMZt/r+T0hWnQDjWHOmhsf32zRenKTGX1ou0PgvvucJ/YTyMXVP2aHol8ZQTaCJs+QTr61if+ka0A3X5BHPGsehv2lwZu9PjxH8h+/lSlstnNrG9KCVbB7EuEPqsxjRXZtcJPSJa9nFr1fP6WcxOSZKo0vFu5R1NJFCGrM7lcbsroh7xvkP1ZY++zMXKs8sH+eZE/vUXMmzP/MP5RlhnGe2Kc8YSWEQfaTlxB/mw+miRfHF2zpUmLGYIRPAqTz0ySCDe407XblvoteI16vAEfdgP9fB26vAebnu/j9095cr99l/t6sSnntRuS/A90po/5mR35/guvTB+tD45oCuzSpdmwGlzR2rfxLAOWcqc3717yqegk2/eno9i5GOf6Ze90yL8kxrwjMP6p5phWeQp3QCP3l/D7uOv7vh91u631H4/eqecWNIE3RHTZ5YzmP4r/q90Ec1i3ilZnnzQIvcPsD0kUZxh9wzgHvHpg1LHeq+MdIIyqH+ScShyh+UOSs/z4q+w/X4s97W9IKdTFcDvQB9Cen2ltQatyVlhYAxbm0TbXbLhjWOEjPGudUJ+DvPnBjLZxkV59YyRR/nZhTRxy3wapybTXqppBj+Z0oej43axA5lTz4nMD2CvkLGr4n3YsL2F60bcN9gT7g2VFT/yB6V7pC/MdquDeGaWUZiKgOhN3o5cumctSG2lqHQ9MbalHqQW0+5jMTpLJm2sXpYfraQkD9dZS7b6Bf+XuDnN+xS9tG7c0G0u8w6/sn354mLqX94uM+SEqnuBzhMTQnw1iFesh4nUvTjUilafJPkdNkkO8wljdzjTCOXO+2Leck+H49NKqsyEGNVdKH2HMYWrCI2yUhszpwflFXl/MBY5fFYKTxCwJ/PI/fUjeBE6NncUOiTp9jvDPvakGG9he6pyy5mX2fYH0hGu/6eX+N9zE0wkcfdwitv+pbsVteaeNeGPllde/GRavfftWuEPHcV0FRUuOwXojHtccCFggjGxZ9HVqCMjYLulhBDWOTNUGRH41uKzLk4Uo02/ZzSX4jwDuJVnZ3ae9cFW5Nq3Hw0XQyQ93s7KJ/501UIz1bFH7029EYAY3GOw3P9kx53o7/HQt4WPBu2Oiwo5ydVOF7+u0ZT1Kc5KegoB5z4UDc3T+jZPtbe9CD6auanqry9KIh+jgkUz9Pt5lTs1+KUZTUGNz/WsvoNlyIjIgFSGjPgOuvWf+7eePmZo+RDeE3Mvpr7Vnx+QZtcw8fDK769nj3jt9eze/z2UhPaq/+W9uq/pT0NbmC7JauyD/exA5QmUAaiLFys2JtIo6H5pbFKcg/gCsqbbLv5KxvIeFs+8WwbRFkxp7sM9P1L7QED6M1U3lS7mrjDhcR72JVMNrr4rnTRnoyxmUxesXdK6TsvwDvlY1w/Bde9Y1zPSwrwy8e4viYJ7ZbCSPaJbX78xDEGyLZB9TvhtO8Bt+56kfb9qeJtT488o7teW6z7Pl/73qh7/mnd95Du+QZ9mwt07ei+h3TfG3TfSfG29SPf52vfA7rvDbrxkAWlkUBxaUz9zS8opftIeUB/JriH6+hI3J8HeuXIUgfSLPIA0xCj2xIlfnQtWQLrWeaEz3qV54iDNfzaQXb/PLQPFR/NhR1a7M1Mev9PV6k5ZMifVT714l/Zc8mgA29+W8+fZtiRPz1gYL4ojWfMqD8wiP47ZsO2xWrcJTHWf+hMjRt1JcSD1rQ7/In6fcXb8fTixX0rZT8XY6Uq2uPppSVhv2vZGdyHPXv7XEL7uC82Qo/QPvct7U+F9svHaX/zW/HtHx+Kb39z2/jtHxjCPeizt+9OaH9LQvvub2l/LbS/fJz2dfyNtn9nQvs9fx2rfdArZeIITWZ+j3dIj1+1OUAn6gWdqBd0od6zxWKhzqXaJBbuZ5KFWympdgnKlUqQJyt2qrEGFucGZU5NHJ+P+3qy3O0woj7hLcUjr537S2V/FmlzJFF71OuQ5YDLRORC4pFd6Ot4ZqeqL86wo/+980LGV01kRn7m5KwBy2T3APHYnOhnzJkcHAD7RonhCoDc6y5EWyUrS156nU7GBcimwczQJ+vzLqrnM6gMe8o1LBsKh+WiwhcnZTUijIblTwqG5TcKLGRj9QvKNVluyoXx5XZsuMPVMikrhjy9a0OmK7zhm9zMJz7ITScx0GuGQa8psO9OV/SaA6P1GiPoNUZyqdN+G+g1N4JeEwC9JnDuek0HyBbsIzND6WP32XSnzP9Yd+o3sj6OqvPYGd/HTOrruseZSi52WqEPK/Rxrm3vhraj0DbqxlHQi1vS0RcyPR/7iW6wOa03x/c1Xls56Wyc2JbxiTWOLZPVtohkfALbskBbGTC2NGirTCJTKPzr8BnTE7Y6VXfOVNrZPRnnSyRrKy/hmkdvTYN30+PWzr4Y2ia3UdgymKZT+OKzo8drrMIxe/hs2s9B3dytMN7aKdrcrU+wudN+zxGW4Una/B3Q3sYp2vzR7+xQYXCrBoM7J2ow4HUwEKZobZVAWy0XamMrOcvYUEdCPyDCxfOE8T/GN9MUDS7l0LdZB5fy/wAu5snaXJZDewd0c1l+DnOpxLn8h/Q570JtLgL0zev6Fv6DuZRcqM2lFtqz6NqrPUt7SJ8pZD7QJpFSYD5Io+faX7dZG38D9DekW4sGpb+jSWVVap9HkwA259CuYzLyjL+6MhX9N4P8lfogke8/8w95oSxvvGHnAPqyzEpOyfSa4xcgvzfbN0yo4ScYCm9by7luQ336k8K5DwN/LqQxqOswjztAfXDI12Gshb9+E+VOwBF6wulCXk7jvOH+Ix3sumfdN7k0V/7vM/wVyrPCZQL7Dc9gXAPGtwivHfG532S/Q5MqovQ33C9Ii9wemuSOgNy1CpfdK041ga50QZDaRkB3uWYlFwJ0/FzMyRDeu8U//VikGp9/YSKsp/Js+UT2nJHuJ/Ou6X9jzzjgeutIe8SptUectL03jf7pv2fPnrpA6zt6gb494pr+K/ZMF1yfN9Jet0NrD+QxtnfrTdL0n8rw7DTrRni2/3x8dprdSMc3TR2fkw8ViDnnB9x8ZwHm0cPnNTRGHucnvHe3n+edIsH7bU52v83K7sN4hTcv8fOOK8WOCXDdc6XYMiHAC9/bLjJdtKYG1nlO0wXr3PdxGXDtGjuZ3B4zTu6JmSZzA9bJFQMeQvrrk7tPshwXPlf2O63Mrv9Jr/B3mx/7kf0Wp1A0S5L92dZV5G1RuHW+VPPu28JLk9ob2H1Y59xfQvuX2bsnbY52gBzH57omuanfq3PS5sFZRID7PNhrb+TiuxbS+LDg6hdxf7qgbeli0HvEAn7p4v+FNgEH84TiqVLXE287hOd+49sxqT3Kh5yg97cBXIPudX/fL/L9+Ltb+T0sNnEE7LfMpfvbL8V4T5ovlQz6D+ZMmd94yIc5VE3crflkwXtR44KT0eIF1zaCDlLHL7j2KceCVwbmw2/QU+oWwCfoIRHLgmtjZPH2ECHXR8xv2CRTxqNuI9gkZEEkDGOstS4gTtOC9IFMsH+E3DKpaMGehsabIv5VpExCfKp5t6zKvaC0MTQ/PRaANnAPGW1AtPWXXVxWPcezR9wxCffO3xYwdsRrqnDc+5ouZgR+X9eq/DapsWHV6MNw7PqL+txl9tY0v99E7divwUaeOMdhQP/+L3otJFYVIE/2NkxCv3Gbs2nS5gHhoY+ltklZg+Y3poDN2XpVE5cJOmE0NzSJw1iUx1qNYO/83eEXXhv2Ce/9yE/trY7LxCRYNzPg6QSa48W7MuB7QWqExnr0czX8Sx/e7Ucbmm9ziRtoDGnPY5jDex7wIk7hRZP2yAtXDWL+Athf782n9tcTf9HsL/FreeEF8LxBeb4H+MH8Qcz3tjgbf/Cc1PiD0fl+juOYD3j2+5nHMR/wbPctpmiflo8Y+aM2FuNxFnuh2oHGr3AuMG4lHvnQn7VnrTBuo8JzMQ4M/dRrB3Au8PxrR300fln3/GJ4Pl2BCz4f+5u88M4BbKOJ+kOCumdXwbMTFJjgs+inzhmIt2fm7hhdD0OeqO2vz30l3l7B2OX8V9k1FWc6z6zjhepTEtBpH/CHCPCHCPCHXtTFgUf0RnX+nGUXr6ieU3LKR8jF9mXn17ibJ7nrCWnK9ZJ2J7UvR/pLiphpfNAXv1FxpesMxgVFqgtS5dvnlIH8sthWdtPYoIg/c8R/88VvZPLZQ/gO7hNsmWirUp89Sn1DXzxWkPrZ7Rx5NZdvvljMTENZlmqvhXshoFu0W176sHQEH1eBfQs00Af4D/wsl/JLjtzh4jsnii8MBt3qvNsmVcTNHeedjDQH8Dp/h2bnJCsxmni9PDR98MT/Jd77H3rPFPpk4P1R9x6m97yhosE/j7on0HvLQ4bBZ0bdE+m9ylDNYHDknpPKc9wTE8A+86QjHG6wl9DPXDtPPx12B/3Mozo9zUuCzwnAI2ov3vCwjG0/94gP5fOKPyl4B7/pdZDJuP6LEq+DDQz2Zq4z8fqbSf4rE68dWe3HMZ6feB3jY0I1rtOvqns+fD7myHHGsgpitFWADhBrABmCcTWVJC+CazknFvEJ8B0/15K8IPro5nNBvpzk9XnJnX3LydS+0CSMK/U6ll3sr258mbXdANeQlvD6nJhTMpGDvZJyLxR373rp3jGv50rff1mjSeS/c2IOaU70RxL6lqamBNwmcmdkTrSM/p4Av+dE75AE0OEQ54eSA+7zNZqw5wCe/gT90MYmRzKl62rXP1rY/ft01/+sXMNnORqXGHBs1T2nXqvXXVNjbqUWdW/PHaykMCuVlsF3Qfmuwm83zV0O5OE8iXGN994WDe/odbjG4jm9jh2ra9YvSLjP0ft+er9l9Sfrr1TuC0cifoabNql19U9CCId9Kay2DdBMZFj+SSH6z0NPVrtQzgkf3+sHmZFrIHvCFa0J/nRT0IF7WXUvan3vWP1GwEJpE96D91vT3hZtY7yHe16LdO+1jPHeiVdGv4d7Y5e8qMVW5qViLNhz/gUvqLFKgrjWiDFpjiDGoq0yMv+J6qcOp2Aei63K1F8qrVt42G9aVCZ1gl5QQPMyM+xM72tz7S/d5F928erq7/9Rbdcnhgmj1x3QxpD8ugv9Jag3CX1/pvmDDU9+kOvAYzCJ8wnc11D5O8pUGk/72qc+pEXkcaf/V9nf684VH4D20Je552OslcVgQPPPL7tPxDEjXiPvaqbxNNPsWMfIQ8cZeUiWf+dCXpxKpHAy2eU685Iy3iO/89uV67Isu4xwr0e5Z4Br77+k+pnkGzCnD22Fiu3sWns3fE7O6rVMdvfmTA72orzdCXKXcIX3oT3CKfZI5UnQGwB2RlLmzLkN7P7bbGD326Qt/Yo/FXg+34k6CnEST8TBZE3d1TiuZrIJdJM0icqCDpfIE6ab4PPqcwcVuWFA/cxTOqLXOKhes1dU3+2QNTnSRuuO3RbsmNQTNi2oG+yaxEX6SdnPMxdEoqhHd8Nv9G0bQVfMWZAee2kSV4c6Is6jaEF6o6Yb1g0ePS0vRNlpBhn61h8YbMLny9XAqyNzBmw0fvYBaHPfPkv+P/bZKi4quU4aDtuWYN7NSx/eoM3ta218FuprTrWDbA4ej8K637pEWqFrm8rBk/+islDfz0aUxQ+9KalxLBf+XuEt91nyf3qfteJJPkmqHF4hVl5klHANcAwGWjMrwGP+Ocax4Vzg/dx58B1pKufJpY4XlXb+cTh+zTFug/fMFhefDFJb6eaT+PtKEfN7wjKzY/D7PLwOto/wd6vffBL4CP7uxNoy+/1Hvwq4O79CnYrpT+4WnU75OcDB4PrFC7hvBHiFOAV4lksM3sLME5rehjHfK1+XFx7ox2vMvmw+wfahLKGi3o0nUA+D9l/ZTfW5Q/+r9RH4fGz8JJ9jW9OwLaflK9ZWSagoYv5K7aPbcVTpgw99Eu46oV4nribluiNk6NugXXcuU67nhAyR8pHrvMuiXLeGivrMcP3yERpcGl75kjpWFie4Y8NSx+XPa77kkgjY4QBnEd5D3X8mfgLMS05QPdNlptet/jClN97V2s/WdTmsq3UYx8DimxGO9yq03QI2fe2Xmk774ksavJqOYw2Wj/wPsPacybQfr2vD12gboM4N66Ps7b2o8xGr/mL0Ed/5Jbax35/cr617qa6P2uOajo1r+8ROeWH0C02XxmtBuHb0C22M6br3zZ+zORphjie2sOuJvMoUpuN21L+g8W77IOUvuTQ+aasShzqpAsbRXZj+B00H2M1hPsRnfuTBvKJrrXgxXg6h7dAM/dc/r9tvorLz2Tx8p+3JrfS9nAV7wleN8W4HvLvk+dFjRxguPgbwUHxRTU+scTQQzRfVpPqiUnS+qJRz80XtJpjfXJOH+NAM7SJcX35Bm/dG5T7CfIdyv15330p9wYV1uO4lsAZpyto8+IK2Ng2Ur7A2OpQ2vq9rw/Q56wPtNX4Du3+V7n7/cZSvLN/g6HG0Pc74Dx6nvqrcA9TuC+TuO67Fk01QxhD5gzaGLb3ywl9O0vSt83+vj8cEfYgLuGvg/vvKdXx2j/LdCDSTqrT5hK7NeceZPEN/HMN/S+4qpBXk1cC/kVcjz0b+2hXDXNTn/KcVHMPvpb/XdJNV39TwTVGkJ4029zyv9vVz8XifhveTdGMI9yr2OVyPbdfxOLh+vnK9R3fd2kfzh3M39jF7GWk01MdgYwS4qONT4XJ8GPPnuguPDuti6iaPji9q+yw+304fn4dxR2qOHY4V44602gO/Eyvl9hjGGGFM0aSYlmdX2pSYZyeKJuIPW1KD668adc8nZsK9C5XrJDnJfiqlIoRxs6fSg7gf62pNW+33JgcdK5/T5jgVfX7J7iDdCw7YKmYlg75XkiHeeR7qg5Z8kpoVU+lY3evGmADTAhuND+jOqKHxqwHQ87qAfi/crI/J1+Jhpd+pa+0XoxlB3ptS4dijXCNG6Adjw6Av9Fd3pGRRnbQpo8YdSHFHUC/dv8gmrRsEWk7F/GmsV9Pm6ErZTHljCueF71mx2O+1vmcRh1TQZFti4eZKBV7bkh0XMH03EHoD7s+yd16AucL5qAtY+UlB/tn+31djrvDr/dtvTyKfglrwK4fgCotYa2Yx1SmvtM+jvtIr7chPGq+3iMKMX8F6zHLenpHVX2MkpsYfWERZPuYwAZ/RX+PIbLv+GuqoNf3GqueT0iW8byLpTgvZ5sghEQcPzzXeGJAa5zRJDQVExHdu/8naE/je7fe/eGKRwdJf4yWmmuXwD9faZFKEcWO5prIlWNP0YsPmEzXkxUkX/xfXj8+sNSSZjpF0OofWtBJp2cXGqjn8ZyLvSBdN6QGYV6+DOC7HuFneXJQqJZNwAO+BrcQLrohoAB2B0FqpQeBzJUHeo9y7tVR6/V2m01lIdlVzpq2KT3XHTLA+ptSK8FXP63N25ki70xCGFufy1J5YZSo3gPxCSM0aCKS6B2pTKwZCqcGBhtTNA02p7QPNqT0DLanc4I7UrMG2VPdgN6ytI7V9Pa5fR2rFIMYX5Rlfu/1s8Tvvbh273irmMyE/WPS7eP8SRza6SNdUkdUnsDibuEABw/kiiuOtaTv8xLvhJ6hLzCKZ0v7NDT6wa3KFvv/1FwSMSyxBk4SfhCP5wnP1PmHhPCmawsWuAf1nZipXnwyf/Skcxs45c1K5mBWuyTJxGuHz6eJsFm+RosQQ0T7x8xOXZUE27b/lvBo+mgI2Q8kNYkuqkksG+hfgj9+YmhWU/W15TVxTniy/7SXerV7hzQvBlirNFd40+YX1JTBWS1y82QfVVkmWTbkfVNkUndjobE3LlvbbyqRsz6/AtpLD5ltukghXFvFYyiTiSRUnoO/+1hslWksBcK6JaytoTbvW358SXE28H/wEeJ5r/8vv+Vj8U2HE/EfcSyyNEA74REm6mEzeoPV96R5jt01sJWhb3xMZmX9yDa/OtzIZ86UKgmo9lGWkYj2LT8+q//lGjXc1yEE+lbzelxgP8e5z8etfqdSv7Qfeh3Ln3U2J9Wu/fbyLQbe3pCJf4p1fJ/c4kskVwf7kCgeOEXlQf3IWrO9NlDcNJ7tfjiZz9aeSs14egv/2p7UxH0gJuIeTszYD3aw0nqetuQqHHUkaHEom1PBfw7OXwLOtwAu70x7nTwFvxDzXA2msRmEA+XKqmz6/7PofVw0Z0Vd//8NzPBg/ll3Fd2WLq0wBtzWV8VRreg3vnbjOPR1olKRuDuekBsPtz6i0KomhCQH3zWB350KbHqBB1GmFvh1+K9I2wNl8abWfD7tEhynA56RmRazQjieMdZLqxNjTGly75KAbcxYXPDuSexlE+ZUM8gN573nw2XF+jXteWtmSCZijP7HGfYnyrFB9RvKSoAvlfgrVr6+rN2MOAIw1B/pb1Miee+C8x6nt18RZCnc9xa590DcZaNW5FPHxg0im3xPK9LemXeTfv+f6EX8trvfTxSyHbgurBxkx7z37+icBbEXAf8TJDKLhJPoKESd7GnX5HApOxtV/3hyPj4EEfHRvHI2P6viWyUxuWYtLq0lRKc3794AtZS6zSiF3+voN7tL1te5INOCODGQvCosMn+D+3hIpu8MqNZtn03oXAe6YY46zzP9CskXM3mMFmh9wWYhcjTGaeA1r02B97sCCDGczb6F28otui3QKeeL87CDlQ2kMX9V3Aso7WJ9brZWNdbrRDwNwian5dO6ms9Qbx71VrH/dGD9/kBERkBG9IB96QT6gT98BMqIXZEQvyIhekBG9ICN6QUb0gYzoAxnRB3Khrz9Vy5sAnSoyZu6ELk5Ji9cE20i3XsiXsEZsQ3FZHfFkjOAC+sKaOFs+rXXotTn5kpf95WA/dcqbeMRXPY6++KSiO6cxHLWQO6ovadDH16owLB0Xhoiz3O8S8hGH4+EXbEiIRwVd9ZSiQ034GvXRJlcy2Ko4jid+q+RHJMD4XOHL6XJqzg3GFmcn6HqdIMMx7pfp1aJ4J1fDw7VIJvSlyjO+5Hpau4OAvhROanIto3qXpXAP5y1s+qVzqf/N6qWsvu5z1ebejf5SBS7YPuYNYHuVF2z3k66NfvMtu0AGknzS8YwP2zVR/eUJvumXl1e0yc/wap+EuyEfZGusFWwP1HdUfegUwM3yDYw3lYvIcqnTXFQmrVtYJqEeijrxhNPMfvDCZ8UzCfXSU1h9NoL+S4WX8YPyQtSRjfB8KJnmedqbTgX5POP221EXaE0rk7oNxqp1t9oknreJa07hutmsxMQ7CfBeEZ5FGxZ9M4XElnV9SalETHAfxuI9FeCxbiF+X3xKXohy6cENejsG7AYZ9XT0y4KsevKDXPSr1j2pq8GTGuDLU9zBTIChNQVr7GTYzUVoM9M9dtDxyqgOnklljbpe2WLbsLZercPaeoHNX6CtmTeX/PbV3HLA5XPtA9u+E9quvGCbH9faXLbLTzoup3oI4DPgw66lqLM5wD5DfMhX1gDnvnK9Lu8O5rn5CW2eARnzTypFpKttT8ev2wugg2HtAroPuTrJt+1JVS7+TMnzdUh4HfCl/kWF5uB70MI5JMzFN69z+4Q/bPExXeVnT9Wt1+jyfLLUwWL/Z9RZoK90pVYen7yJx9jgsCwvVGX0GqCN6amb+zjVtgMZIT2pxT/yUZTPwT6S2hNmRyO2jTwnHHnEv/IJXW62EeQJPIfX8b7++dInNJ8a9F3P9o9sdrMh4C45o8qdMpA7GfQdD6w56oUhdzbInbL1AXfvQK07O5bt/puo4oT5j2lSdstNIHdurMKY5gD3tmPO3BImd16+SUIfv4XcBXKnSJE72xW5E3Y0O3gJ33nRyStypySIsfBe4o41J2m6krnsGx+/gOlLFqxfn5q1fscp5G+HaB0IU+pmtvbA7xY8NbInElFtReHj+/zCQ29JwhGU+fkxVf6o8O/+uobqS2gbNitrweDdHqZx2HSPsMmR/qTqs9Tg1zbMYmv/U3mSeUqTJy3UJ95Ga3wQZewXNuriVxVb1nEC5QH0qdrG8Cl+hX5tZrt7QdYsu/iDh7f/cQ/VgV5uiMd7e1QnT/D8j3Xx8mQC8EYp4Z2ZSg1KtPHnpdlAh0u3mwdreNNsr+PlRr3/rygy9eToeXxfae9oFH1L8frSpIS+Dp5S4pkJ05cmrY8f385TjHaSYL2sp2vc6noZzyCPTn+I4Tz6ZKMOHG+V67QYWtAbVvMczbkmH+6zFEXTqp9Pioi4VnRdvBHHsPxqbmjB3jCuYRM3G593mnN7RfM1Jl9owbGwOdcodYI91J/SEzAXmcBm+iDX1GSVZsJ4zH8skyaQNKss/80xzzpzicdSJ5pKbVInQd18jUAMQb4gdfYSFoefRvfYFmKe63TEy7LIvzmbtehDW9UqeA7aq0c8F4rNkgrX3SeY74v6V5Q1u3fJCmHjQI1754C+Pp7FaaTwPUc8rN3mrz2p4aH1m9Hr92sF9wOnmE+c2s1fsj69MLZlFz/0MNZw2v7UoxTn8p8cWwekawr0tOs3iTEfK/ymIXlhivJekkJj+D7W3UU+bFPw4IUY5uhKlKe//0SCLE7S8XTAnfdDKk+vVnk65YuHFPgBL/dHoyw3wvxRhR/9soyfuxrJb9c4Xv11PE/fF1V5et3V6dgf2eRmNbEZT1fX51BIW58GeGcH4D3ijIdvhXVIsyIeeKzHxJkk6DY11frQR2mybQV9ZKujIHXrYkIeuRrbngjXM8jvv2ckz/AZYAsUpF6p4M8jV1sI1oL5Pa0ZfL3VBja+zRlOsl1+fZ5Ngk8Fr3rD5u02CfHqArLte4hXG7hn3CpOIX61DDDbEr/3p7SH0I+B/j/0ZVA8WbwnhLiIz/Ow5g7FLr6PbAa7+HAgmdadJk4DzSvHNVsQg0/cE3FgLb//Ju6Xl5N2bCO2jPS0PEC4l59Zq8noWi7g3niixg3PgZ1ctjJ0AvdrCyIl6FuieJw3gkMloGsjHnWmBB2xx3X1V0bsKOazxNriFsVnyZ9Qc1++jR4evZrRg02ccGKTG/O8jcBXMk/FxzNhfdtdir51FPeIUoNULmOOw3RdTsOHj2kyHGyEaOUpFt9CfZUB2xJLMId+LoM2FqLup1uTqbEg7wnPljD2js+B8cQC7n7QPZq4snzVz4Q2G1yrJ4uzKa9Q39/4OfO9xxQay/wax9jO6m0p8ixfR3+ZsQB/kNLynUG01039zF439mP9vQyaKywcecKPui3C404YL/L9Pyv02A3vRsP5S1AWv55qW2Lufcl/fclG/3LA+STAE+HNdL8HbAtrqrt+4zeJfnWl/sM/ixwGnT+9O22pkFi/Dv3n1J8eqJTQhy7IPTH0pwdkbqBWzhoIye6BBrliAP3qTXJwQK37jDm/3cNga8ntA2q+b2KdaPTPY21o1Re/q3ZEV8rHPtcQPI8q4JiTvoL65J+p1ctl9OFZQKfHOJNs+7KLY9XI2+d0ZEutaQUSrYPVymwhs5IbX6vEYawFfoU5MqrP3Us4F/GWVXAks3D/ItnP6nG2F5pIg0t481JaqxX3gZBfmAciWNPZ1bL6jVx+wT0U77E2TUGgDHDLQz9VvwLoTfxIbdjQJ7nx+YuFcT4QPmzDer9uD7khEiDx/hHgMVQHGOudBpBby5T6i8LH1TRnEPW7xOea5SDfbN5WzeziTyJotwU4mzNAjBVzSgola3FOVUFK9hJzzUSfJcVWNSe9BO2gfKCA3lp3Tm8tKavITs+WzI/e4FtlWIc2SD7mo8JYKy6ILqqaYwR+B7RhvNFWhTon5upnl17tY/b3X5n+Ob+Qwr+SU/XM6ZEDSn0cvE/m+3OtDcwvclUj84vg+Mea9xoOfbRPAd79ZUD1D3oBdoTcFsQ4lzkdNmkZ8b3yAPwvJ3fXe0lB/TO/UvHnhhHfjxfGch8poL5CzDnBceAYkK/Hj4F33qyrJ4F9bd9b6lP9L+2Px8vEHbJO31tf7Guvi5e9DbSOF9b1zgoj3entfaCxCNBXL9BXL9BXL9BXL9BWrz5nDH0AiXlj6A9I9BXQWlIE67Fy+ay+QVEE96K9xAp67DcF2/fe76P+j4Txe1X/B8aqPr3UF/xV/PjxrIKzwYqdieF1zJTP/gzOPVnJV8Mcepq/cfJtWsPKBDoAISvCLyryajHoKHztDeJGeq6cJV94bI4PecP2jFKfp/IbH0fPTblBqR/fXeCp/B9for8669cJ88M9OYyJevo+H9VbYI12ParqLfeKnTDH+ehbXfC7WtRNeh7T5r8Y3336v31IG3zlDaKIutRrJ3zHhzT8QL29m9YRteTXwlizgT6OLrBVmcuulgJuG9jec8SdQ0G3sHCu1DpE/Rz5HHkoV3s2uwrlufmWH0qeTJtkfsoG/WVHOuSx9kiV+k97WD3geWZWD1jlsbhvifuhdC+U8u9nRPWsC+Tb+rqjztWqvXWFHetG4P7sEOgXfKpKs59ETAt+GDEuuDrCL/jnYx1gN2bCb/SjtIEt5ODcMQK/W+B6Dj4Hvx3wWQmfRQt+WLeYcze64XMJfM6Hz9vgcwF8dhN3Y+tFQR7ej6APBv0vHMm2tqbZpA2Xo1+mDK6VZaEPpxbaMt9SKpng00Sf1+69V5oN17NiTD8Eew2+X/UKxvtY8t8ISyDfdhXK8i7XFsOuar4kn+IMMTQVWigO5dN9NwtpKsQaf0dh3rgP20FrT2fbAxdRGMTpHCjbEdcrVms1RDmaW1lgXz4R15/ppp1c+0A/5x5sTTvix3qUUdIDtv0/c0Nce6yJ4waauayBFs49sIOrGGjjggMd3OaBLq5noJvjBsNc1iDYMYOHHtHqnGLMcCr0syeo6NQAY5pvSir6lpOevn6so130Q2cYPgPFP3SSoqtBm7k6RgBmoeKrYy0kKxKAT3V/Qz1Dk9WeKKJyrXVqDT9EuNWEZM4xkZC7hbRTW3jthTU8rHVk2fXXVpHka60IM5LszVV5uspbA7Ya/tYjfP5uC8knxV8Gtj5trPjnN1jrKKPqjXCkeiLIoMkem8QXZVSgbbZ/Eciv4olOwJ0I1pDuIlyMnkkF8sxc5pJ4jovlsLUFO7K0iofvpPjqID6znMNn2bkNeG853AvNv9q5g7gHO8jmXuHkQbC7/+1HOS7geyMxRW346QpwLI4IY5vgP7cT/cLwnBf+y+HfAv8eLqu+n9aP23YVRybZMdYTa4fjfkFoYtD9VPHEOk/0sGje/5mP8MYReTUAa0L3VUnWOuHad0UrxzWWcD1R0Btzc1T//S9H+MtVwmWrxC5TLf9gbTzP2n0B4t81EeG1z3y0BiHWSP14qV+F907gNzBmnO9ApyHEm8njbhxvJtAI77GJ0clBHnA6yNapJhffOToZeNnqdB/mgNC9zMEv/MJz63zCQgfYMbfAWrIazrWzani+e47YTXoeQ5+P8PFKP9boUcdvJRt5T/dzIuYRXxhU9bi5ucgv0U7ju5+j5zfwAYc4LzPo3gHjWlSSK3WYwIYAeW4uOyztNAV4gFFkCPQKWU538h6ryHyWQbeBlDqRzt0KnetpnpDJip9rrj1UbBwg5yHN4jpZXBagNWF1pk9Y/2OY435p3a3pEsBCQpr21Dql/aV7ReQR6x57WzQCDq1JquWrrn1HOdunzTkAtNRJ2gdg3o+i/tdFKgbsMGeUFygbbQFNLrxAfemv5nKkOJevvE6MAl2Y977v42uvF/ddQOv/j9DGzRkAi1Ce6On+o9gqg94X8vnM+9eP6BMrfxm/9k2gpwjP/VJb98Ej/vPXaH2jvMLcOAHrdp7c7zdfuslPZTeM8xG/Gmf/lA+fvRPWwdO9CfrbMNIfl9Af7hUn9vfM6vj+NiYD/sM8aV/QNvZrwrNQQ5t8ALNegFUv9mHmSAnWrlbt9PdF1s4QqQihX0FY/wOf8PHPsIZon8MUcqPtIjz0b4mu28f/7RcW5kjAqyJthPmsrWeCfMA9McIHrOLUMwHeEzBKiCtrLw+60a9vxGv8Nh/GxHl+u9Uh/OF5H6/UX7tEmecw6elNBvoHGevC/Cka94znK7x2xPeET5tnxxUB96KupQBPJ8Vf5Jto28NnDPnnRqW+BI0Bffq/RuZN4bL/MdCtAjxfO1PceVHAHa//X2e3zqgBff/jMOGeryUkxe4BWiRcTx+7r+EK7kU1Fl9Nv3fQ+l+3RfS2dO38q+P0Y3PZFAnP90DZ5vFcK/ElDqCN18JN3NY83KPxtAHPLblW3Imyb/FbAdl/nRVhxHL22hxIO8K1u0W+GeiSnqsMcu7aPaJd2CYIC2dKlqSUarCVXEjDM6c9L/BtOaL5mn+KxIr1b+7L2zJxq9BE3s6b873fiMQzI0Y8vxxoMAfc5u1OP1/rFHOmI50z+ttBwGYE+kM6RBpcM1TrNnJZkaqFfxOtaYBfJbNEAehRGArwGONSqcCbLL4ySJT6KTzwPeQr+7AuHcoDHSxojjDQshnkF8oslC3IC3mwH5aB/Fyh0FBoOPG8nNsAv7LBBkZ9wFZVTn4cQV+vgfT2or78bk0Cfco6Xxvg0CIxXl8OjDqP5/q4NbtzVP+FlKeFKR9Lp/bTWHPLpPmpJr8xof3EMSfqw5MSxr8zYfz11Qm+Quhjy7De33l9BPFq53CQR7qkOAVwpfmnt5ZKLQqtbhzGGFKgw5K9IspUpEd+pBZiu7OuRqVHwLnL/kdsof70Im8LqQhT/fyh3VKKbizGdKDHHUd85kvfkZAeOyl8ClGfieXoxof0p9KicGSdPwT4Y+I20+9rAYcQd60cnmndnSusvwtwPz2rm2TVmfcbJaF4MsgHHEd+pIMEw3x0p5+eOwI8UKXJlstr+BLyDG97WB3b/11N67imsFrVmWQT4DHApeQKybzOSOlx+aUYB/VNLtbB5Xe4AFa35G6kdaT/6Iex9KGN6Yn6/Oa/vCOZ/+L0m/dX+8MGJsP5Dpt40IA27xx7/3komwK5NGZ9pP5NnvjCFap8T7fzKSBfAAZbkN6b/9svGnXtfAPXSi6hPm6ed4mohyw/L75+tpFj+6ddwHsQLggnBpNrzgqTNd/U8HnyM/yFVdp6baQ1vr6BsR5x4ZyxjhOeD4djQ11s1cVBd/i8x3mclx3oGOfP/C+WXJw/jo2evwi6COEy6vA8890ZTA9S+53wjcYfK9PxXjxt8SU5dG/aE2B87wF69ugtEfTrkcVlQdk/xyo8tFdi/I934tgw74DxPuJEfLYL6VXCwtnA+4wPc8SUy3hfRhXyHbTRiNUIespe4H3GqiZSlj+n+EvgfbOA990/aAUdZzGXVSeTG1aCHhmh8XzA87CeLcqTZRfbqpLBfjp6HshODuNEM+xtsMYWjtGQmcZxWeg7aNOgHop0SvX/n6u1GN2RW48Q0LUt+WDfh7c+bQNd2wi6trUK4x7eCJdV8UW2isl8mbTfaZMMPWVVWNcuh+Io2FRTsq1TgX+irthCOOpDQpyF37EHgObAXqsLFP2wlzDfJKV5fA6f2TIZcedijFnlcfwGeCZgrnF7wZ5BfX0Hwfr7Fmc5x9GcY1W33nlKz0/m2PcRRZ8YRju+bOWEYcTzSfbk4Ro3wikJdEDQ6ylMmmCsvPJ9A3wHO5LpqTCGSgV3950BXQjWlPEIm711GsbhM7jVr1LhxgHcuvN2W3iAW3sYn936dBnA7pj3AnITwI4H2BkBdmUVkx1Gaf/cMoCdsQpjFTyeUqlSGYP3THy9YaTPg3RP7poI8+fbgoSNi45lLYwN5eYBoLsuNr5RvN173mi5VT6Zya2XJWVvHHiZJzTsR/5s3l8I8hRslaT0h+lekjXdibXvESfR72AhkbwmYgPc/Ke4g66xx0k8aYCj6Wgr0XFZ0gJuqksX/TDG/Hi8E/EH42Uain/YqO53msDOM5BI34j/q3qcvSfMv/l5gjxBn/jJN/2Rnynyl2sHOHG9YAf3gh1M45HAFu4FW7gXbOFesJ97wR7uBXu4D+zhPrCl+/AcBrCL+/CMDdV/hr6z0bEy8bWTVH6LuIU8d+0A4hnw5SO/8wcGlPwx7nHQkf2UF/Fd11EeOUT5L9BfdFgU/vCaj8ozsD3M+38smXP3SjAEeubkhgvi+VPJhRp/Wp40Nn8K6PjTKlpfd2y8wXgdxJsNE86ONxhDlog3x9MZ3lQp6+QdpY9Mhv6M0J8xyJHrrFygzaHYQA5LUpqO54UFyvOKJgLPOwb6XjPwvGOg7xnz57hAB/RcCfjUEStPCoCN1x4zfyT7OeJ0Id3v6wdd/7FZPrB/60CW1BSkGpcgP18Feh7KrVVkta/m3aUC9R0Y8LzIlVRGmIgmuywngnRd+GaXuJgLqHtqucsT9KeC1LrbiHJ+oyoT7wTdeYfM1hXXdLcc5EdgiHIE7EaVd2yZWOMeytB4R3+GxjuWVP5/47mdqC+VZAPvYGuzISMwUicOcQv9EohbOK8m5fxTT7csqnu/+HuRMPo8wybdeYZtXwNMv97ED8HcsbY4nl+6BT4blbE3fR0PLy2fwmWfP4gye5L96PBIPEgujgtlMp65irYO6lWoX4HdKplPMnne8E3QrV+rVV8iH/e61DZe+EZb/xKuJ4w4MHTmUTfvmCGiDRYGnRxxAu1JxAvhtQEf+mwWpzD8oOv5TY07eeLjPJ/J9IflMu5d0dyw3GVDenlybjbSmiFmI4kJ58/jfGqBDq3J2ny2fIF6A+pdXlf314/yfJIWT4F+gh3EPcIPX/5FPD+00ro0N/r19vT3V+l9PqK4TwbbJ6nWje2YPwGb+uQ7/v4vAGYKHThwzSh+pkcY3kYCyG/CQCvMVkA/ZcYAtRVIelDvg6LwBHv6gSHMOTGCbXAN7nuBbZDeR/3/vxiHf7+Z5A/+Pwn8G9qyUJidG5zFrxmcsXYFriVbY9BTYT54/hv68jyYO32eBm9vZpDnm2eIxycy+lDxQeW96HdDuIjAsxd/Hu/rmv95kNos6EcA3KU50CgfUeaNyMhvkY+JsjEcDfAYV4Kwhmuxrqi80MH0OWv5RPRRZ9PaUHo/Nfqo0Y9dHoH1x5zK4sukLaD3GLmMCPJT9Fe0nB/g+S6raD/N5sn0JaYnNbAcqlxyGms2ZTvNvTYJ4xf3L9rmXxXBnDeW94d2FdpUzp+rNSm7qW+jNS3TT+tEYGwa+jdgLV99UFtLO56v2r2a+jfsvbjnrD336wfj9vr5Qw+Nz3MwTzgcYTxnC+lZh3zH9oASwwLyRl3XO/sAF6KHRdT5zPvv8887yfzOdJ7AJ8xULwy4kA6QBpAWwn3snGMmkzDW6OtwBumYyjtyxNYklJezMK6f4mWi3cxoZTQ9eGOJtBChtv3pnyWcnRWLt41//kA8LWTGWJ4g8oWOrx7lMS8Z9WAO9FHv+ZjPxHT2m0+x68mU12fY0X6deorREN+WLd4cVX0Nt4zY7So/qUgYkyUaP6ae/0qIb48ijj0fpjhmtYnmiYBjTVeK4hcBHmMVnkJ9RL/HTGwrp06ocSdeL0i1LaG1/07XUFmJsl+Rl1e1gV2Qk/EozecB3cLFaNLivI/0OFg9BkOQxVsXBVvT7vUzWTA7ZlDs//8mWS8D3OtBjtYvIxWvPAD/sRW6mhgkyCfuKVgiuF/Lcjs8k2r4/1a+d08Ge5dj+g7KWFP0TikV7CzT5g0+5C+dZIOPV+wn9PXzYQ3uG0+NhjviweeV8TBfdSoe5g/eHw/z8lMhftkplUfb9P6bAQ0PR+trJYTVhdD6z6A8+cHK8Xny5ytG8+RWanOgbwZsXuS5gYgP9UB1f1RYeAP6LiP8DpvYf1rxzezYI+r9Mqcr1X2mLCfa/C2kIjpM/SX4fXMY7X8rVxF+UNf/cbBdW6hPfwb1jaIP0XypjfpR9mGcKYVJZKCF9AwIwMs8gWMinzNbnA/2BubL8XyO2Hk6yHy5vEPcDWMTijOleYq/z9OWQ/38wuoMH559pclqJn/DGaU0Fhbr/GBdIG8y7rXO9YVlUoS8PhnrPGfYKL/PLrFSO0k8pq7VnjAp/t8A+mCjnCpL9X63fwZITqpuzVLtKFty+nDd3hbKyWsAq/aogXxK1+3V/x7fFrpu+Wjf2tFedSylkRF+BTxq2ZiyvTSol7lK7JUbY7sZL3OPyHXbf4+PQ9t+OhqHFn/J8p1RD7V8Crod7lNEQLcDO8wTUfyvYDeh3xZlnLAwW5oa++54f/MYeD+y//Hg+OM+cd/ocfd/JS80kBVhKSQvLDnCdNLMpHiddIIJaEDRI1SejXn9KD+O0nrNfwK58supvBVw0IC+8q0ib7lSbDME+C0Tdwv43Z4S5IuiWwVPW0jkrTMZXX1vCzw3SzSlBHiP5W3AbYdoiuD7+D1HTI4APl/bKSbCZizc6gqPjVd3PZBwXnY4Hq8O3RsPk1BY04eNXJjJAgfosekgCxxzRO9XQb6c1lnIpuf6EnJRJIP0TkVa3GBQaNFhFUN07jdVeQJdIj2XNRnnDzSbo9QbvLZDRB1vajLuu5RJvAd4z+f4Pn53iMmfYy5ruTS2XB6NyweOJ+Iyk8t3/VdCLsHxeH58aFn8/Nce19sDF9uR33eBXofjIiQcENPQr8RFcO9o8efov0mz3/w582Gh7OY/RzuowykUZ0ht+FylVVwzIeC2fh7COj0OVfdS/drIO//8XxrvRD64Q+GdHfT75nAL8M4OUhGeu0zL3V11HtrK7sgiTynwJXeMyrCybMpHGe90R5gduhfutcc2wLxQLz6QrOnFqAsjTuNYUD+m9hC1F2faRUMNv+zit4UHaKx2m2Mq2nA6GuiOaDJjy+eKPz8wtj9/zedn9+fvuj9+7ujPV+euzht9+tct1ebemoZyA+a+I+JT53xA9evTs1uzqW9/AqXR2fYdHM6lrGqjcpanai+j3rjqC5wf73ScYbId19bTViZFPTdJvxg+JjocYIdvK5PWFZdJDo75Lun8YH2RBtQcGd5znbjKGHDzfXjmGxdJImHHcnwecN/eB9fpu7NFS1/Qbb5liVQcXVLF3m3KFeiYe8OI678Y7hUb5k8cwL01IfcmyQP9b5lYVkWas2mcSSd5n/KDHBpn4B5AnV9g8iiq2gHoM1X9pai/YFzDmn8rNgGsXRjmvGViKtDmDipPyWmkzWMCb52t8KXfU5oNg47jcRilhih79/gxjV8npz0Kuh2Ou4z6nrE23Lny8KhyNgXyX1UHHAL5LtxaIq36BD5Btk0YxFjyTB8BWX62djrSRvy2V7WcrnWrfhejUfO7HLpb2cd+zOUDHIug/yV0+lE388F051Vy7eGtTx/zMh9MWED/y0TSnYf+F77omBd9MJ2kJ6z6YTwlN0l8DujdoGt4cmjeV7451yb96tGyCsR9nE/O6aD7jbCtajJvk6Z3u6osMDcLl0Fls3isxm2cbayycnsd/XLYYb7GKBl6jgkcOQb20aeVVjyfkiuj9ijGShjJjRHMFZ76VYA3kbcdPD9LdBzDeJWIgPSvnoFuIqkUN9k76RG0DcMn8J09DuMxvghkRARrIuAzyOeM+Dw804F5iViXp++PfsRj9HG2fMrkddZ9Z7Pd6q6meXQ9m9wze2oU2y2L2m4PKvA+2i0vRF0deQzo3s5E3Z7p9bi3H4mquj3q86puj3p91t26ei8ngyN6e+gkw7Wniv+fp9ecjOdLy46zPJ9awPl5eB6oEtuCdDLzUMh9HOggAPSGewUbv9L2S45+FnCjXb5l4qsP4x42nvkqLLxOUu2wOL8o0MgSLovts1Mavs7KcovQnt/mwzg0jEEDPYfZFfD53iI1n85CY5VQNnj4XrGWjoU49y+6CWyPsssV/uletzBDWkNCbuQZjN+kSchDO0hPVHB9Fqd7V92r7Yfi/qhw2c/EHUyOhIX1C+h+6Om7NP6ZnAr2e6gUeCfbD22h/LYnjHiMehndT2V6ZUxQ9EvGm0olxpuafcIt2fRcI6ypSZptCm+6kMpr9k56TN1/qgV8en/p+Lh08OQmt+lUzSjf4+V3svd2wjp7gYcuChmlTI6L8QaUwz3hclw/gBHy7AkIN1dYXOcqk1QZveXTwIhs3vJpjVuFPUf2Ooqibwvma/ZKKKOXUz1krygUXyDdGQ3xD3yq4Q7SRPijkLvlENLxffS8rLWHkY6XClbueaDj1Q5z9lLR0LMG6HgNzO8xhY7fDmNOAKPJt8J80ywx599Ik7B2mVeKJYeRjutG6BhsCaDRK50aHadE+CarOHQY30mJp2+4fpRe3+boAHtliI4tTH17OyiPOQZja4ax/Q3GdgzG9jaM7W0Y225lbEbqRxrph58jrgkH2dgcV4qrKI/ZM/7Y4B0PfSdhbHDdQa+zsVlBbrxfMf76m6Ob3Hx0jPW/g7136httPfS6+c0fxtv7/Icht/Eg7tUHB1COWGEdPZXxe11muIb4sezi1Crk5YEjQarHCUc0Pa7rTA2fo8T8qXJWL1vndWGc8rnJO5RjeTFmt7C6lUWK7XI/1dH/7B3Hbvl4qd95x2i7pe2LR91hzI3mMF+3Q9Ed/sZ0h1sXSMI1wCNyjom4z0I8sxX63B6nO9BaUJRWt0VxbqFPGO/E+Ect9rHNiXoEi2FkcY4Yy9j1r5C76SOmT+1Y/ZPVrWnVNJ/s83sSYly+YHNpUubyecJcAl9oPpV5ii9rLBg9kdCuMRoPowt/FN9u+BvMs2Q6wIe3qXsvWcreC6/svZQpey8lyp6tje3Zgtze78Q9W/QHZEu43i3Q3qR7xsfhxac2uWvH4GE/ul05X/IUsxnxPMboyRBv7MHfNrsqFxAOGST9crSFCM1VsGKdMx73+lHPRvuZ6Uvu2L7j6t6fQ2w7jnFODmlVQryOKiOngh7c3B1yq/xNBF664O7x57I7tskdjo2ey68VWG6JMf1sbPtsNA3ox246nkgLQYey1uH3gRb6+9DXU0b3AJJltCOtVfg9JKOeWgZ6ayaN3WN2RgnNy18lI/+2SV3D2rr3LNbvueF+PaH79SymGPfq06ownpjtuRkrJqOuP9eo7LlZ6bond7M8SoxNL/+3xoNUnaPzQMjd8K+zx9fzTxUBTJPsbK8seDPG2GNuE+Y1qTXHEvObhBmb6Hmgaqw9p4u1/8etY9Ue84VfHXXdL2bCdWFw0N846p4kWuBeULmO+bataWE/46Nv9LEzRq1SM1cRrQRZay477C8BHmBacHfEuKAgwi8Y7uUX3P1YA4dx/HfTvQzUt1poHP/dEZDJsRz47KRx/HdHrAaM47+77kIDxvHfXWc2YBz/3XUXGTCO/+66Ic7dWGsGu2mMOP7aC+Pj+HkDi+MHHS4WGCOOPwDjCCfVuB9cjfH7SNMrBDyvDXNJthiAjkC/ctB4cIzht+Tjd8wfYLH8zMbCazIpfSjKsVj+BmZT2nMm1MC9sXMIn7hVyyHcAXA7aq5xN3NZQRUXKw3tMcHQEwsYuIFaQ9ZAyOAeEKH9BkPFQJMhONBs2DzQYmgfaDNwgx2GrMEcQ3C9wG1ef/ktaqz+pvDaJDLJC316yWbKy0IwjibQr1sAPxtv4KRKQhy4ZxXmgtEA8TrboN/GNA7wOOBA3tZ4Dyc13sRJyAMbCzkJ7R/kf423cxLaQMgDG6dxEtpByAcbZ3MSKTocpfzQViYF3IejKk8EORgJFF8RI0VXODMNWbEQ4EnAfQXISvgsvsKp5ghgjH0llVE2O/psPYhPRK1xXBTkoxniThpHdjnmW/pQhyjnsH7CbPvBjBq+IDD3Nkswx4efbL/bm9vB9QwoOXKuNpRNTE6zc/xgLN34O/SJS3j6f3xdGIcP14zw74B/kwHzXrX8U9OFNXwJjM9ctMdHuNucAfKBMwfxmHsSlKkPwno/m4f8Fa7dGyaZSVocRs5MMZoUwLglmOP9kRD93BvO5reJxJqiy8ebYYf1Ds4imb5y4P/oA+TTA/S8j7WA+3zO98QSDs9W4ZWceCprHTznrm+m8V2YT+il9R6eT8J64EVeknOZyM5jZ/myAVIWifeLTYPrRolQXS9b9HiwDtGvri5H3C9PEz0E662wd2kdsWu7RMHVJ5KixHay7ST8K6zbQvP0M+E9nmsPCa4zol7eYOwJ6piYm7sM9D54vrJlSg3GXAVlOd2+E+vGd6WLXph/EcCc5vnj2YoKv2kC3Fh28YWAX3thLa5X1gL4ioGdgcobsmLx8Qd0XyZmVuN7sWZCRpBHOON3vF9pVGMUi7yoxyJ8m7jXC2l7AFviwfNQ2/Bcs1ym3zThp+M7wxfkEcL3TuAfL+XcJX3GpSKs/cSRIZbQ2Jx7IhMAbsK1BwDG3bSWwZhwbqZwdiGNmCic3U7BdVp86XYijoZv5kNT09GGzfTNS1dwanKAnpnmi7IagDhnu+IfzyN8Ecv3nJMQSzQTz+l1n+1eB63jPfr6jiGM+8IczYtc1jYlB7Ndn/84+p0XaFwiw/Hl5N9KLfVPAmo+ZjfIWdAn6J5bN+gjoI9H5nhulI6SrJePw3+Y9ITgmfqUH6j6nlaTq/+yGv4zxUeAeXh4Nh++v/2WbVQ3XbRkbD3bwrEaBIs88TokzUNsU/IQdfNqU85/RN8TrfvCVaz3cJt7kbabAB/xPcDbSHOJxceRRc4XS3kdTPDM5WdXc7RuA/WF5Fq59mhr2q7R5x8uHnu8VmW8WT+IHy/iQQbppucPmWZ3O5l/heSyPQvE7cT1mCsGYD08AKez5w9fP+qdmzF3K+E6EVJEU61NwjoaiAfCazdIoA3xKk5hvYTEdmopXn0RJo407bpjrmhMxutyGHQOoK9jYu2CY45mh1L7zMnWAXkK8hIPHaP2bGiMZ2FNgNe05eFzxPu2d//cFT7zU8fEhjGebTbbHvaQab2Y5zyn5HqpIGXekiKy2BkuKqvK9nT6SMtFCXptkwtrRPKk62E+7BD5tCCFJ+GYfOk21/AgE/v0eLqRxvqVJ9B+YYTvzhbV+L3dBrTt060bk4JuPB9qFcgYxEO+M53GGNH9zU6b5CWcc/kVbH8S9ZcHYG2W62L/RIz968gTd6CMLS4YpZfz59XwgsIvMWYY9LhIuRIPk5OsxP8puk1eQvwf5np6usskbxLaJ9mwnvHx4JakumoSwJjSiGPmtOwqtEXNt9wtWYs3PIy1Pee4DgPf6c3D2GfzsyEf2jnE8/tB4tk+yHc7gUcWSBYukgdTyvcCXArS7rod6xRtcB8IEM/fQsRTWp95XsC9/Ipd1bh/kB2p8481R1O0RpHPZRG+I1skIzET90S6Cc3Ri2wv2z6K/rIWxdNfxzdKvVKlZsnmsnj6a/4mHj6MN/7iLPnpo2kR6752E24gTIIj+enLEWfJ5CDywjnNs4EPcq8ch/8w4eph7PVnSkbzwaNGjQ+On5/e5Dg+qO13Ib/cvn2bX91PzfKMnZ+u8sushaPz0/Xzp/hLFPwlCv6WXCqGzwTOir/z4V7HGS2/H2PNmz1s7C8u0saeR2MRAWdj8fJ+ahR+K+NPpnoU63MVtBsaNT7t/mK4X5lwf+R9oLkNQ0HedOYs78P9VXC/H/QQ0PlpXeQN32CcF9aoy3ZiLTUWf2WT0LZAXybuO6h7geW/3eroprY37+omm13bfsjg+jAX7KNn8gx+6lfrgVxVkhCHFT3iN1+6y991CuuPa8+llMTHYS35wWh738LFx2FtOLWJ8oKZnHu9BWyTzTdqcViynGlv/gb1t0yx6RvU6bj1uAbbi1aI7pXyQp76Nrp6+ZY8cd8gxtt+QOv7sfiR68FeyIrwLTaxZVDZC2yJiK1p9/nLFT82zv/lH6jzdtM8O7iWi7VGhT9s9QlPL6N5iVfdpPmx+UyYf/M2n7nsIR/6sRnf2zNQzrUPlABeq3qn6XKmg6K8qD3N9KWDX9fw4SSLs+trnJvN6aF1pLrzC1JsS4j3y4oiEnFYi21V4SLgWWXbfebc+31q/i/meE7AfE6QbUjXhJyMk2Fou7TgWT6z02m8Vsi9JMhys4i4vyrDj2fABebbnNYSQmv8XlVKdDR5bbxcxVw1dt6NE/SiAeQHyy6+q4qQ/TqdiYtR/hBG/tAOelI76EntIeQPh+areCCHny6eTflD6CKNP9ys1FnFsWnj4oHeymBcer1l9Bz3KXvJUaUeB+UfvRr/6FkYzz8aEvhHz40Jfk3EMxL5WTfQ/DKw0xBnMB6rJaXGjTY/+n660TYrvjsI/7koX9fAvS5lnwVjttDeA7s9uINrjwh9zUAP2/3sDEuU1Ran8ND7Euhm9WHm97x6lilHSu22LdHXJCfAPz1gp/PoI33oPancEFznNVTQGl/CrT+WZgVMvtSA6bYGaKMN+m7igg3CkSf9wnO/9aHcpHWD2rC9a6QC3rZEeGiPJPzhJR/uJ6GtYSJ1PNitEfQreDx7xJnkcWof1BaXRXBcVPZOx3wrjIWYJTadH3RXXbtfVM9VvMaQ1dsJz80zuNejbldiyBoc4oKPAa7MKYmrbzfPvgrk/8xpGOe01OEpcUmezCkSxoMiT+rEPekSq3jgcswD/m9RuHWxxDddI+64KMjr5ck+6JdvniN6ml+iuh+tT/LQm1JFsbZ+ZprHvNi5Vl5Ha2zhWdae5mtpX3ybTbRPhfcABk2yJm9wv81TeRKe+aEf61eb97NnaQ5qW64fzyXDM1+PXsbwadFNWn/NoFsGSxNiO5IYLtOY6b9f6ac847EZPnUebcDjOrieXuGVgz5h9SSfhXP4MN/6itTIbVkGW9XO5Bolj2XT4Og8lrsbu3V5LMyuiPj19fFOlJylvrkSa7OyKB7f0Ze0g6sIX8Kz65UGwFlDTyRg4HprYY3ZsS3u3gZDRW+TIdjbbNjc22Jo720zcH0dhqw+kqTlsGB9l8SzwMfLZwkUF0Rqlb1PImNu9N1U/zw1HOBrAS9Qr9PHOiBOdsE9lFseT8SPPFwYPBbHv9X5A//uA/4NsqzChb5GGr/+8TI/nvf2oFuDAdiq7kXh5/xYuxr5ZDnV4QslGFvsgXFqxewD+TkrkAM0OPc2up5P/7ePPlupPLtSe3Yq5U33KPwt+6z8jSdnhDyQYS1KbHboy9Gx2eh7DCix2U19Ne4AjS8upzrlzlNj6ZR7fXH172+Mx4/aUzr8eOVN3yI+od4yjGe5Lj4uRL/XKfGFo/XczHTQ5Y80+jNH3iuN0OcwHlmJCfy2Ng5MADmq06exvReUWoLoa0EY4B7x0DCrRSSCTtSlxOMj710zIC9U+XT5AM6nhtUYeO8uWOdXfLhWaD8D71oNfKvP0zzFb+7N9O+ejjxwnr11eg3ljebeL33UZ3hhjXv+JXVu4bUvaXySSSiXTM5jIsZLCM8dEwtSjy1GvxzhFlB7S7yM2TOg7/eWA26AjZLbxrUPepPmPiysvsInvNLpEz7+BeYRzBH6XvMzH5bG67wX19A8z1G2WUCzzconMNtszQW4x6npgJgLOZZOiz5Nup9Rmy3ePCEYZ5/lTcA8dKe46oIAzU0ca+/EkQr2PAlR2wxjcGsnMrusZ4FyJhvw1ND8uyO4P6/uy6MvHdcb9+cb5m8Cm8omTqB7gNlwL4vm6SGuh+YXxDDWppzbPMhz7X16uuqG9au6tVTCnHq0nzJIZCq1oTx54tQ01PFgTo5ssfIC3KOZXeXp/lDE38Y0tk+De6ss1m+viPyjPzXA49j4kjzRZArG2W3fBc8fOKPGgI5vv+nkE6W3eWfi7beevAT9A3AdY2EABlJqwLakxBBsaALcEY5grYr1vnmgA9Ry7b0wvl5h9cU+1Ae83Oa+ctDTAcfCy7mKPqF4Ypzs97S1+uYlP8430JzPV/2ZyRvdDZTPbaD6gKnJQXkM+rBV3wnwwUbmQ0inucuVJobTskxyvUmmhxF3E+vlZ05AvL1rNN72a3hr4hjeRsl3wNt+WGPA/eM0rt7FzpZBn0K/U+ynuXTXjFofzFuagLEr3deLNxsYrl6nrMXNsj6+8i7KOw/IY/JOKXE9693x67lR1q0n6COTXPHrKY6y59KtE6AvtOuwjhjC4ngCLE6h7tF0tST7063CQqtkTg7S/R8cn1CcCutz2Im4bEnaW90C+kIT7lVY99LzJoTidGnLxLcFrHkxc1pJFcYc8pVOcc61s0Hfmg02UHvAWrz8YQvZRnOGzEUXg77l8BHPpzHiqRsw3zJbItG3F4PNGxRu3Qsye0/eBrcxiL4P4kmtR3/HzAkBN+ivQY7scW1Irofv7euXX1EKdOQG3fYwreOcXbpXouexGbIahWRN/uD8M5X5q/M1y2OvvXk44I6Oqi/hUmrmvMtoc4y11+Kz9WuZTf2v7xaOox/9fYZ/kTOBHk9+6G86o8eXfMBnsCGxVks/8JEWJdb0lT0+5CkNcP16A7OrPSVDIu4N6fUTVb4+DGPqpnFSokjrQan5e6CL0Vymh3ZLbzm0sVhG8p1YvFQb5U8ukIN50kwYX6xgfNu6GfTOfTKzrdGuRvjPhE/3Dey9WpnVrBfeNPuR9pOH5IVszxF02T/8HmyKV/1YCxZhXltsczaD3WjOLZH0fmVqN/A2sWkw6A4Z1PM0bqH0tTs2Fn09Oopfzi2IX5+1Md36HFntf/mG+PV5IIb5QqUgD/LFF46i/3lPAGPRTX0Yf/S2YOUijn75Rqc5920R99Qx14IjC1ay+COsZ5evxAzNpt+XH0VaPObAmNR9vawmF4s9uiliIrOd2A97/ibap4M+z76z62wsFno9QmOP1vTiGaVj46M7P6FW1tfx+Nh+/Wj5sBPak/3EiX4zrPeAeiqev+P9iq0h5vehbXxn2lj61t2j4tY3fF1D22Wx64UR3P9gtkU6HeMzeePQzJtJ/ssTxoi+Xr1c7e8N8luizD5HXtNwXj2v8iy0C5FfqXzKXDZbmnNtmtRE0vMtZE8e8iNr8f0PE89nwJ9qgT/dDjZEOvXFbnCXwVxK6pFXIV9am4Z1Sva6kB8hHzJv/5LauiRW755FrpFSQRaCjIyCrGSxRc/V+kC29oFMBT0wWCu81g+64SqfUN0bV3O3ILVuMfKVVpBvTM+7kvnQM1WZ2ObkUb/jOCp7l4N8Bl2mz5v0TpVw6630LMFZJOpbS2NkgaenfQfZh/pNZbbYSmXf9VT2NSv+9HK6rzia/4XT0L8UpfvYVF8Lg92UwWTg3LzRvtrar799L6BExnOh0637Us9t7IuxnpZwUlR1OqE6DPIszSo8fb9Sr6nbgb555Fd24fcCsdY5MKZ0y8Q1ILdmV1mLH3nYnDsszplxWDRnt4gW8jeQV8fy0GfPfPQ3xjDPVfXRIw6oeMGRS10FaXfcTgJl925wfxognjD10ydPYvt+KKuwPm4b2Acos7JLHx3TZ98AeJ5J/SKFEeB5kbBiq3pP41p05+Z1x9uAZ9urm9o/Dv07E2LKTibQ/zUJMWVYu1+3j+CVx95HwLY/dSTonnK87nlvQttmRR/hDee2xjtPYj2M34NdLYHM6BkQXvnYJ6y+yOcRfiwJJzsBvu19sj/DirGAbM2bHA3UN11WJXzvebCfrs+1JP39YWxrX0aNm1j/7sC98XJDVsQuLKB8Yea0+6uw9hbu2cy59nXRWjyrymPANrbTPZtlF/8X4MK9YFv0xszX7BHNd/jQtxYk0d7FFu4PeV7uv/KFhWXSBvfbgAdvAR4srBcnIB6k2ZkOs8K1I0M5f+6KsuocrmI96i9NIAMp/1pk811owBo4rpUOA6uBgzEcPGG+gmUXZ1clgy2OMTvJmFtmYPsA8ybW8Pg86mlqHRx8j9b2NGTVdysxOe1zlHOMR+LDmvJALwhnwrsYH7b16a3eC8jvhYkkUMhixDYuZTFiG/0sRmyj39NdSuvgdJ0P/MDA9s5wnNg3xqK0nR+guQ4WAwftBoEWv5FQ11drTXjPr+H5HQ6x/PwgtRGAx1gT/Yf4Puoy8P4gtBMVHrse+OSg1NonL0SdLnCC6XTCCfZ79xn2eyfoJsB7fan83NuQ71JfCfBe5LvJn4/lW2BxrGezQz1j6naPjvh7T1w3jqwC/WHl1YlxrJf4JpzQ6Nj8xmxJpeWz+WluPi4vRB60E94LXnc2vYvFMNZ+vsn9wuc1yp5GFt3T+MdVyhllMH/3t71/DN4/NvL+Onz/1+r7x1idHj5gE1f1Yz3BOj/l96CHsj2PPInvvkEsh3s/UXXS7m9EvT7afp1eH+3JLecqov20dujmcD/qoq8d9eXP0fY7GpIwNspNz1nBvC+Mszug7HsIR37rRz0jTPO30E6bHKSyGexHlMsNiv8HdPfYt+vu03Tra6X87MJ54+vuT1yVsLYPfSid+obZJ96TDC/XRhleromy344Y+50DeqSnG/0CTvH4lwGe4SPL4zqb3kT9xd/UuDu+1uwD1aeEesfUlMd59C2rvqQLn7Xh95g5CeMFArnow2pQfO1Ib3hWkJ7mMgmeAfLobdgXqwv8duXO1Brqh6JngSt+P/PYe8m0PnbPNfEwC+v3j//wnK/CHg+zjm9YTt0ovXGMtcIxod4ofnN2+VaR0H+nHL9mPd8brd/av0GdPj3CC1ZxZkqQxzyDNV+CXgm647xkTZejehzocMhPUIdDnqLqcObtP8Tzfhx6PY7xexvGc9Wr/Gzm14nxz5dHMsieqZiPMc8QoPUZRuKfK22iCficp5LhSfIJjHl2SkoN17PC6WD/WDhtpOvjnpuQG9uvg8/qJF97djx8NvTX85jLpeIb4jjujcZyxucjOUOb3HcO1Yy2/2zsPTxPBWMpiHW7I4frCdiFWVVNNBdpK/UjoG6OOrq5KF2a8709IIfvexhrKGH9JPM1/xJx74v5EGoHSKB3maajo9ztoPrX8UHUz//m6vwS+zLbhz7BPdHguvAn8sKCgOk2S9Dkw88mDnTxP2zz0T2Sh96XhNdO+bCGJqy/yJ8X5NW1GzqKcHBQfjcTc/C79yj8r0DhfwUS358vGtV6Af1nRu33tudo/I/t927Oxf2CcsoDgf/hvsEftvicNo0HDiXhnsE2v7nsVbrnS8gHYE8c8jdhnYxKo4T5xZ1n0B85i+Ya41llmHfsqfxQxNw5tp+RKmFeDj/Mcvi2nMHzYLIvp7h4Htpjz/g1Gtx2Vj9klNYUVHTavj/7E/Va1I9nntbicc7Ft6nS9fFTY9E10y3r5oxD16BbpltH0/VGPIfrDy/52HlB0yLMl2B0NvNNovnZBdKL7gRfgtUmvgD038ZxERPIGk/lrZKpbq7P3NvrwxrNFz5rlITH5vlonjPHxVoHwO5RdZyP/x+/8Mq7vqnAS5DusR4L+quOnkA/M+iqJ9/1o5xHHVVYPdUnHNX2A6LHtO/CwquBj2zILZEfpz6XC8tOiabkGuo/ZXMJ5PIls8Xjx7DGf7cjSmVy2pydhnU8sS50zpx2XxXqs5g/a77mMNDQT6k+O+fW18GmeT4P681ai7OpTov2DtNlP4tZuL+B7nosD/eccfzM1r2xnnhm17dxSEcrXKirLqN5nazmgrdXzevco+R1NouGnrCA+/scSdN8HgLLLTSSWRG+ySY2Dyh5ndZZ4lTq80hXfB43snxNIVt5/kZ4PlsU6PPwfeR6Kb3uHWC5nujzOBDRYIhxhqdA3qKOOSE5SPVmrInYpdQgbDAE3d3K97Xw/SIDq4kYMNTwVgPLp52aUuN+AOimX6lzZjHWuFUdWpqh6tBaTUTUofHZ71ITEfvCMbQkB/hMWp+PCyMOIS4ZTzP/Rf33xuez+wY3ufsH4/W1Q8r4WgYZbqj7YkzHjQRyOC6I9ghHlrtOEdVnQ3WPs9bNuHmkboYc9lDdzR3bXvYrlv+UPb4O/ODMBNp8zOkjJ9fxiE9YE41Y+3R22I00Zi7ODnMdBv4/W7HD9urssPuYHZYbGbHDLNzfqQ1GAtlgix8DWfAZtcGGhhkO137F6jioOexemEsG2QvqfCTM1wJdpTIZHEhl+fO4f7UP93BqMS7BKeLZlMKtP5KWpTL938gtoLnKAcAzxE/hKPNVD6cdWzzCG3BNwQZSdYEm5A8LI2KToheg/nv0q3iZhPKIyiWURyiXFJkkHB5DduF9jLWoPiXdHIu/j+2P2FCvhX3lhiBM3N3rpfoLvFvdCzwtz4fyzWPgeteAnmc2YA3TK8JqDVN9fKSDnvl9Ga1hiranAXkxYWdYGQ1Zg6qth3ag6avRe7Lzks9tT/Z4Eu7J3kF9esjLs9+t89NYFipvwMb8IgFeH9/vV+eG88L5IVxwTjjvF45jzjTbT0W+2QY6AI6fo7XVWO0ptJO7+tHfwca8qKNMomc2AJ4g/91fWkZjuvDs1RaFfzC5nx1XF0HVsTeCHR4eVvlPxMH4z2zxwLDKf2aLHcNBtjcGfLc4WlrVoDuTo4GezXA4/IvhvSI+Q/OMr7lRaphfMODJKZOwzi6tk1Ci1kmIiEw3tDhD84ejuBa4Jup6YI4I7lcL/bh3+rqSP/l7Eduj56lnfyriuW/x+ZN7aZuY9wRjiWYOa3CktTR6wDZVfBA7hzUfRAj0Zxwz7snifizlu7jfR88owLm5aV6KHre6AJZmhRdj/A3zDfBOjE1geebZupyoLJafAM+8V1o2cm4rwhpjOVAGePg6Pz63v3RITCXHptJ9WsyXvvVvohr/uwzWiM9R7NdrD4peZS4huE7jPY78yt+aNkvS63BnZjF+1pp2r/gw6GzI57LyUM7DmD5h+eTlrAYFzSeHtQjTGhfqGubexNZQrXMBsBEWzpIYvPfo1vBwFH04879g9euEI7/0e3Tj+LkyDowhs3ALaE2K6L9RJpeBTH4LZPL9IJMfBZl8v8D2IYoVmbw1zHddqcjS58O8cKV486Aiky2zxNZ/6/chFJncpZPJwOemDioyuUsnk+F68qAmkx/4N8utRZsJ6RBpE2kUaRXpk9qmEb3OF3Roet/94q7Z8sKhwdH8GvVK1MF50MEzSMbl1I7mQbclqAOD7QDfc2h9D2uVp9tJ7zEdOJ3t82Edi5JsuiePZ7oJf8/320+jj6W06jjGcHVv8/Nhp9h/KkDvmU6ffYyXwBj7Qc9UdYOKyxL9a4TqBueaf4m02kDrfzp9Gp+0DWo+qtGy2T5KNgcdTD7/VKyahfpoxfoX+ta51/bJC2v7mNzdiPmmtay2GJ6xt2XijVX4vVZmdVE8tRjXoNgOrs9EjGt4APNNge8cj7IzOFmMTJsj9CXaz1dSftiJ5ziUWMXyY6wGMK7x8ZMqT73MruohKE9RF1kFvLdc4Zc7Y6y2UGuMyRbkzc0xdp/VjIjk8juyRSvooyr91sZQrnc7kG7LOS5KY8EV2k2k2wWKXgTPUdpFOIEeH0UarnCosioygPo6XA9jvUILdyXr5zOkK5tCVxGgqzqgq4iAMp0jsxW6+jSMPIbty30WxnoyQ8PBEbqa/xnSlU2hq8/ClK4Snt9Hn/9M106EXm+l1xldDX2q8ANdTQyc373TtflZZJonH/R4IqJw6+0S6usHwfYrh7WzAE9cBHwG4foA7u2AXWg0IHy7HR4q87AWx2e0poS6NujzUdfEHI1bEwfiC+hgPlybeRgrSfVLo737m4Bb7d87jPQ1i8bHdHzDag+0yDXund+wvUN6jqOypvNgnFu+YbyjXKGH0bnGzB+RRG7O67yryIE5xphfjDnFeA/PYaTneF32sOgI/MShnMnVJ8zYKGJ+MeYZL5Kzoi9PU30bM/KTAxjXbAs+XczOK9xgrOG9pH1AIFnQZnF+E0fyG8jmwSbSPugNlDkxV5d4jRX73biee/vMZXgmYoH9ZrAjKgk3WEvrkxIvi6HOm+MIPOsiRb9zYWw42qzX6fomrG+6P/aCkitaSc9upPnJLuSBG+j1pXnJgaUOA5lB6+HPKblfpOeqE1bjGebq0sfDLpqmnre1QsSaATg/GpecXsO/egXrv5LcHRmr3da0pWImxi4Dndgu1Z3fg7U84fOUocYdcPtdLA81LyGG+8esZjMJKnMx9GlzcVCehTCYe4UKg8T+BTqvBwwBvqG4sK6heJprrHqbFtATjcZ17qXkEntyclDJ58uL0FraY4xnFfC3ElIx4CHBgdB82RGaPy2CNQd2TEA+kuFEvQH5F+YsmjEuBuQE6h/CwnlSyMjySpq7LH7zs06Q89dKL35okfoVH0LxgkK6fgTWPzSfnblyioPxz78ngrZDmAtSP28nKZWaHUQiGIfM1fB4xrjaxm4uPj6B4gat47o0rxxwZDHACHAzBm33ob2FuPR80h4/RwqsmJfFw5inxsU4xNd/NPc6JTxzMpyBe5o250tlhXS/GGwc91HgLbLsdFqSsqvNX9mkZNKbZ0mC5zKOOcwkPX/mNNALM4zOmdOMVdkOWczmp8G7uYOZZCBqJB8NmshH6zz8MdECv4sXTKNxXKEUVvfKSnKpXztQJLuaoxYJ238xpu1ZAp31Ap31AX31AX31tZAsmmPepDvzEWN9Mc53JL5XieuNi3+bqsN3esY8w/edZ2r4ty7T4zujdwPoEmPhu/Pi0fguQBtWgjZoVl8OcQcRhxCXEDfMZYAPt95GcSKRFrBW/dTzwA4gmwcaiu9xYg0SxOmx8Hl5KtL4wT7Sf4WWg93/oT/av8f/i2Gb5Cg57OebFH/jc5t8yG9gDL0wll5ov7d5sMYNvKcPeE9fmMYR/Thhnz1xbNni/KGAQqNv9GF7Dyi0+cSlZ6PNuyXkj/NH8lqZb8ICMshCMFaYd84pKZBmEvfLAKv670/RalqhHj9LycPYN1jDG2CNce1xzLj+OG5ccz0efJf1Z/bkPU6rR8k/W2SJy0NFWbDrEjYvCx17t2NtEjEpPCrCclRn5OeQniir1fFJGOffeDsnMvlgteP8FlF4YDxrcSP6Lhhc8Mzs9hYL6QlhDYU5JSUUTqIBeQsBGnDXs1j6ooidcC/PAd4yDz5z6LnUKr2PzUcFykcdY+LMnQRz6JscScoaHJqkwrtgJOaiHH1bgLMIexzTcJptCeoXc5RzrXfQnJh0PB+Xv15Zn1VyjSpTHHWZmqxapJNVD+hkEvIjzD0yEkbz6pnPKLtmEowbJPl6mUnzwYuzqcwvV87NxL4uH+kL10ftrxTPHXQ1xBLj89LxnLaRfPfpgEP6+PNFmQm1eZTzWh1q/N2UhNo8NP7PETfHZXSOd8PcMpS58U61/hLyeG1uZcrcyiS6P1FcSm2yDWna3NwXjz03PQ0jPSwnPXE0oacH7pz5Iuar8s41unhC9GmVYxzmLfdIxIzn62Tkezn0p6E8MAat5NJ64ikL+kjJEjt8xzOPEQbzB0A3D5Tdayd31DsG9PGJbF4rLhoPPzTd6j/Fj50pGgzPXDg2DBEurZgDFy4QHXhGef8hPz6j6mIo++g5uqR9HX5aQY+bBzSJOpOFniNhcI06/+uihH0H0DdQj6pSxiCQ8ogqMwhZXYjnmiYHNroMQMcIU7QRH5yo4ViLIktWJWt8Wuh73V+rxKuhT/eFr7W5TkqYK1HmWvu1vFCp7+w06fDd+w1fZC7Kpjl2iTL+qIy1os1SHujTgF8DyCdpDNFZeKU6BoRPnZmNgxtFk4nyxClOoDHS143Jq/YZVPqxOBGOKC9ApsZsZo2uyykf7naovFLN+SPkTYCvAPA97EI+ZwD+xviuEWRND/Bdrh55qh2+Q5v170/QzkGPq40+VDMig/BMPGxHrcvE1mzvSHzHJHP8+ptkHf84+aZ/0sR4/tGfED/sKfnQz/fPEwnWCW4opeuFuKbiIPD/eiueQQu4h770zVMS8o+HGb6lTxkL344UJAe+yTWQG0ZwjTtfG0+rimvDKGdviLDzANg8HQTrjtB3qA/fNmVsH75DqTW2bUJC3XwFN1ZOVuebBDhhdOJWHa2zbRhN95WGGree5i14ds3JA/6x6Z7VWDUbNFpImXw2uTDP7jHgOXMaD0X+ufErlk8FbVF9gMbJ6XA8BLIE6U0AfLCQzWHgB2GQ+wFCrgCd+274L8gvhzmhrbeY9tUMOsFe+I+E5tP6K/G47ylxSlHAv18Ml0kOmvMxT/EPz5NG+P+ksflknnwufBI/DdQW3AdrGgZcCxX/OxxfF3uW3XESbfpsMedkwN1JjBLYOLGZJ7Hmd95ZcEDD96xJ4+AB4PvmjLHxYIUpnj+ofGrq4PhrYAdZgnqsunYqT7TT+vwljYlrOvM0i0OhuW1l2YAnY8dM7VNlnoJrrTLDNepXPaOOaex3F0fZmNbozxA/Hz+Yv8H7fVbfDH2H6KdvTZsxIm/RD9Emc4MdchatdTa6ztkzIvNL+MWhpN+50A9RMZwVbU3b6FfrnR1KTaxdViXiubALFBrMJPkR5IMMj2x1CH9hoUv69AKdPwF0MgHWoDLwpovuvxBfGHOYKlOC7krOPZhCpsHa5keGZLRH7gD8nBHDWLdBWXYx3fgQ8Fi52hGocYXlXTNG4j+OrPZLSj+yLN9g/uouKZ1cQe2pSoa7kexF6VKXrNHt93Xjwnl7GG5QPlGZXENtCAtpx3E2Io49cx6b5yScO/z+XIEHngfURDZTu9CZqvF27CNyvsZ3rQHUy1CPR/g9V4h9Vgaw5lF6hOcq4NoZeO9X4Z+naXYJyu2jHNvHaqK8FWWO1zEf4+dSRmKY8006ml3FMX4mhJ4FuynffoDORS5MDiAMC4PICyopLyiUWtNk/7KL5eo50Xwqi5uTtbOscPxY8+lKZQ4WjtGQBfpq+AERG8D2mKnQZ/D8BH2WMDjjGLYPSMx+5YKOWKpGp/tUOaD40Bn9T4/gGfTbB+LzebPOPwv9cyyfd3PqWeh/wtj0r94vnaCuzxX2EV0GcBTh6aG2Az5b3Ij9zeeCq/2k9iE8h4wjVueqNMwRS7fPM1Dc7UOaa+KyHEh3qAMDvfUBvZ09D3jERmT6qqq3o42m6gSiga09rrceHpMmxMODB/2viKsII37AOB2TUtT9ecQhv9gJfEaPP/VJ7L46p05cL7nuoVrFx+fhONQ/HbbzlDrt1HdaDHhWBjDKZjnchng8a1JkK+C4S5UX0RIr4JpRcvCjca2BnrmIz+99mtHenqdxDMvRTwnw/M9gqdYj09Zn2TCrS6vOaUnG2ee0nMTPqSTBToiWzIb5YC360fPpGFLn0+1g8+ltAJnccIDyfLy+XZnntqdxfgEYY+cZtV4a3g+4lsP91rS7/Mh3hDeT4RP9xtvCtH7CyT1+bLsg9b7bAS7+n2fhu7i+K8TOYdQVcJ9ALqwEOjeX7fJjvP7MabuqMfeEH4zX/2ZOW1ON+9y2NF0O+JkayoOBJ0cFakv9rhD5vAXsBuSv10VYf5VnaG5/Ptg1zkyyM2whG8OM//Aw9jv9OL5yrgLoZkUjjlM4Uuu3AE1buCzq1/DA9z9bWFszz2COBo77TBjeqfPQeI9p+R7Qb8xleQDX5Y30zJfSm6To0Gj7rs44Mi8nriXCEdeTwTkDxpDeiLBmZ8shjDMa2T12ffrbddU3wz09bfycxPPwK0f6KM5HWDN8YWfZGofi8YXVwLKN4AvixWIScKMeKQwOA74UVo3g/0BgRBa1p42eh4PKedsovGkYZHsQL2h6ABcwjt5/8CwogvlQ31acPoC6QIMcHOgC+Y/7Dlj3NAw6QJO8eQDlDcr3NtATOmT3YCfVEzbT+qf9oB9YphAH7lPMPZ4VfYfrGdEN2oeHWfwk6HLDck2e97drQD9YJXZPzopZUmxVbRNt9p32AG9JqRPwewt8h3uRxllN0toki6nxB4TuLacub5qUaiSm2x8k/akTmibdeVWDe0IKMT1gIKafEqMoyyVOgS+TuidzkVNJzJ/xUsl8+LdK6BM3T2E+q7Wh6cEk4OlgS2V1T7RVYf7oqclZjclX1biH5aLCYfknhWuTuqcs/+0dLuG31a4zMthuKWXVlpQV1aBjVLdN3H4VjHOOiWykdQiF4iuk3cB/O8lavnGYiI0fsL3wVKPFlBqF8Z4P4x2ymAIpY49XG+s98P+w6PEsFdsmOu3zyArR96FtifCH66QGEuA3kBBr//DY7TecU/vVtH1Z3nXDSPsnC6Q7ATfTyVCfJSVWTfvGmKf35tOzDNtltn6JY6rEZ+A+1ox4Rnkmsd0XQKc6Nbn96f5JQeoDum6EflCPSLKHAe5TUV5PzgrOSgZ7O2BbMY/YJHwf78my1zEzeeniy1PU2NKHxZk23DsG25rzOu5N1WJOdwA+DVlR/gYc50Nf5VPcA44p7TF+Sk+sZAo3gDVZPFOyBrxTKgaEKe0DgSk9A7VTQO+d0vNxfrJG1x6QtSgXUd7SGqicrU4dk7DwGonwXuQHrjr1nWRa7xT3lHJBJ/b1TwY84zCG4HGf8IdXfHhWykG8Rp9ro/UrhccKfF2TWSyVMPglwHCVX+h71R+COWycjGdAAz80nZphfnabX18vaokCZ+TJnbMD7vDsGvf27Zb87dv5/D9st1Vs315WYX52te8CUlo1uWSedDWZZy360FK1A2x5wPE6ArDwkh46VuOU4EDmFKDz9Yt9WH/QNKW9/vTkiqeEpMtF4eR+fwOMoyB1xW3mKcHVGOO5nKj5qhPtHVRvnGo/lVHj7p7cHvaasly4v+sly6sDv90KaxOgvspHRuDKfi85M6zTX6tFkWBM6NzcHCK7+Np80GeDPPQLeot/NcirAPJCH6m+XXDFxFqqn0+0Oy5ifQsJfYd0/Z6f0O+hofh+18pMl/UCXtYCzJ/RjQvjxEKT2iP03OrpuD+31H9GgTu2dcLA2i5ITae5Qd05KF//3Rea7I5kgly1En8f338dtfXMH/nompZfEeBhvYOkJFNsnoG8PRP4TybYEEH3vhnx/ruG20B//iERS6ZvcstyFPScdH/lBb1i5QVR8eissqqjs7Amd8PV5rIbpGzPNyLme/KOAnpGCOhJg0ayYhDPV1NxGfF44zCLYUvmmP2IsTVxdaOSM+3s+TdgHlkR4c0Uv5F7fcDEFcTQH0CS0S5JsVu410NYK8Q4e6uAeS9WzueoUODB2j/ssvYrvrkTzGbWr+/MYYDn+rt9gIcR4bl1PsC5IOBhL+Ddo4CLfUJfk1+Fa4mtht++3VuI+P2H7dVLtwN+X0BcVTkkMHVy1yo/b5knFn1YXZ1Dqqd5mp727RsK8jT27rlHfObpdaKwcIb0iCJ7WoYwb8/ibPxBodj4g79IqVHOlLo8a4R3Lh9ogDU8+/0SuJ8zzn0r3OfJUw6e+B31A6zPPOW8aa3f10a954nrd/T9nLh+R9830X790O/TjkuUfmcOxOtzDYUBic+xiM0pqOsmA36borjHKSSlgu3VEj6a/I5ArHNEyyVKXcjQG07EAb4bcPgT2Y+1oRCHl1+g4bDlYg2HMfdx/sWa/aHib+WFKv5mUvw9OiuzGvHX/MYNEuIy4i7FY8Tf7tmAv9h/HeBvhOKvB2svAu62wFhnpj7uboa+2yYHV++e7K7pmLy5r3NyTx/iSZMZ8f4iexPc75AfyjWX3eIDO4ziHeJcx6wgPw/4yanJwUcBDwOIi8jvkK9Y6HkwvLNh2CvBQjnfTjsmNPxgmgg8PNhw2++kShPa+VXVwt9jYmvaYV/DTRUSaUkXAyaLs+H2oNTwQ048OgnhivrEB7mmyRjzgr5O4lTr+Tbc9rDUMOeXUg65MdJwY6rYUPgwfC+NNVxdJzXclC7yZoRTgdNBhqdWXgD29wUFkoOUXU7IpqvNubkguz8CWD0l8h0zxVaAkdfU7ag0oS5oGwzA+BoKKqSGG4OSEfTnTOi34TZOtOKcCldA+9DH7emimse4cUqNW6WvtinITy+yG1MYz21Ne8/XId8B43joCvosXDPf8pCvBdZ+KtH2q+A35qc+/HYa6E632qSGyW5cl/XAk0EnCuTC+qyD9Rm0gK3nNVlcsE5gNzx6FSF3RDBusDa5BnD62kjDJq/U8Px6aQK5IyjLH+Q2fD1F5HA8ZCBgJh8FMskdvRbylz4reaovhwz0hUxZsUqAe/Nkd70J3mn4J8z7h0EJ16IJruFahDNxLR5SfIZYl5OUOEhKuDUtm8KUz7SIq0DmZHseBr75F1jTR0W8nme0LsH9B2HhTInP/J5I+Cf95ltypUrgfQ1zcJyPwJrdG274OkVsuB3Xb0W04fcA22/Sxe6kZwDXZoIOnSGxtkCPKbmIto/9BGDNsB9sF+9jTB/2h31hn2pfoHe7Ed8a3qmQQiYu0nAbzo135pD0GK5pww9hHEqfEwzreNCPIt5J7gHcE7gTa3aDjVEO69SatkeMTq6gZ6EgnqOfTbj2PdET7hS9kzY7UF9DXawuqukSD5wfcC8lj189b1INf2DyM7zw9H0+aKOXkBy7hdY/T7WrvOHoYMB9EPlATrp4M+D7DpB72OeWOXOqzD/L8E0g/fR8m8AkrI3dGTavu1ziQ7PE5kkBN+b2YH0j4EExzO8xklAAeZIwiOvWH0Y4IY/ol//mNN/yDqufjrUjcrLFxYNBoJM1joZfBOC9tDAH78H7IQu8ex9ZS/cpOKC9OxP2w0zkv/pa026Rjs665WE+00Vrf2eHfirmGRcsMa/7qURrHlvX+HnvDMCHJHhuqYDnVZgv/alYDs823A38bBoRawmucwms83PwbtkSfI54kkV4TsrO/CnaTW5sQ/jedtoOto9t0+egfWwP28X9tIZpjCfPpHVtTGA/veNEfmymdluyffmARm94b2hYl8/246VSm64+D9Ku18TlWsgxAfPhaI6osQb5ZQT1I9SNUC8K0HMMrVUnBoY13Qjz505quk9yRoA/G58tH4PPnhpE/T74KOIZPcNcOc9kPD3DQx7X6Rg7QcfIS9AxdiboGKLjTGxYp2NsdFm7FR2jh+kYR2OP88ivgA8EcYxo76Ae3XVejRuvI+/BMSP/QX4WGKxxJ86RnYtKcitPx8tP4XvbxOU6/wLSnYn8LjyB+IFHFfYh/YEeGfVifj6w/fmUBn0inoHg6XiP0dzJ3ZTmLjytwhrthRn2LQaku6evNptqeK8B6/xfa98J11QebcnAGk3/Xp0JOiXKmADHaM9E/L2k5ApaRx7sHqC/D/1Af9Xmn+3xTyAsb0Gk9Hc4bP7oIT+fc624cRLgZ5dKf75B4eP7wEbfROnPzCH9DQP9PQ30V13dL892msswLg3pb3YE4y37iUJ/h/X0tymEMu8+slriqO+ad46mv7/D+K4FunroYTxzitJfQxrQx5VLzE/p6C/TCnRTAs8ZqzAe3VyUJo3Q301EXJ6M9JcN9NcsIo/F50gJ0F8R0B+fRvkntoHrhe1g+4z+4DmkP2iPnpuG9HcTo7/kZKS/K6I4R6S/frnahXPNlIN8JnkddKOPgXZdYklG0I1roOr5VlqzC/Sjj8C2LkMd3x3zZmj60dTJ8foRP3m0fnRg4nfQj86i35PQT1wepd7XzZOYfdTyVQ2P8l54LkR5QdNXNe7MKOZOesEGr3Yt+obhIN9xrRjCGk0JOLryK00uLIP77QrOon8L22DxaSyXq1Xe5G6h+4DX2kvO1PAj+1dTkGdk25fRM5eJ+HQxxvIT53KPhfq3NoCN9eASMhJDuEbZEzCGioIYa15YZKzAvRbga7GSEd0j4ML5ou1tUuaMMZlzutH3eYXdcSnakrtcvOdyrCfB4zPJ1Edjsx9U9nbwTENs1zOV+ddald/Jym917+0F8l3HbQhi7lxhUVkFzTM0uXXjblLGHYgfd5iN23Mhjnuji+en6sa9K2Hcb6zGZ2deqo6b/e66JMBTWYx7whgDB/i9A/hZa1oB8l4a402IRNdyAnx//7jqpzl8ww6qx21z8QnPvKw8Y4FrMvq+6FjYvSd07+P1DhjfjskVYUm5jrVDV6rfXzviu1f9PnjUjz6Z9xXc6pjS83fHlPYID3ZgyRSuF21xz5Ss3vIp7l7vlIpeYUp7b2BKT2/tFK7PIxNH5xTm73+H9PjVGCKg994meXNvm5zV1yG7+zrlir4uOdjXLW/uC8vtff0jNVW1eqrI66xDNXH175Hmpw7q5etyqVv3uzXtTVobNTq5PSSsn+/7MFVeCN8DuH8S/rqG1/ZniHeU3KTrbrNvGcEnjL3nnctLCI1vX4v49H0tllaMowNW05bRAa2n4mb4Q8/vdo3gURPDo+4piEdOwP9LdHi0IXcsPApdFI9H8y/Cd+n5E7mVX8TLP70OgT6Wl7+K1x+CfZr+sJsLjCmHxWgNP5a8PTWZe5Qk9MdHr6N5XMLgaT/y0OiJII8+kH75/xzo+zCXbQW+eEMEz/8MU5mU6WqYgzLpf0AmZdqtRpRHaySWh9U9hj6YCnLueyBn/quK5y1MHpVfDPJi9hLzHf+iNUuJo8HP8zMT5NHFEp7J03A9k0cdRJVHYZ08ygR59C8xm7+YySNoQ3BFFHk0ewm2TZ+D9rE9Jo+CTB5lKvO+7Od0fv3yVgfO0QKySLWFo/3f7scZT79C3ar56wT95toOMRBX7xH3A/5bxFqNqn9M6k30j7Ec41MTgm587pBK54AP5k+m+f7xJfs94kdQfAiONE1Gspo7TEZmwjoePV+1l5l8DE34Dv6vOP9B+oAmHw25HpJDx7rzy3OBXeg766YVX55dNy2BPvsT6luu/GIsecpqEHpTatx3pmxyo92l2mBNoKuKX8kLsVY2xnv/yIC1IZLsB0+PlrenYmPLrZmxeLlljp2r3KrB86xcuHeTKLeiJuQZoC/xlyn8Jm8MucXkK9h+cfJ2QxT3ve6WaP2Tz4fj9qsF9cxIE4vf6flsOG7/HvOBkIegf0flKchP0NfTalZ9PdyjOaRwNfp6kM+M5euh/pwEX89Y/p2ZXwTd+AzKNqTz1rSZYOevmYp+/pRebWyhCxFuV9gxfwd9QdHP0e7f43cQ2+XmslypBPicp+stEX3IGPe8R5lXJujiqFeifnk23bL5NNjOXQp/+PjnlC+Sr5EvpgFfvMF5dBaef3Asji9q578AfyzQ+GNbKuOPLG6cd5aP4o8pcfyxfIQ/zlqC9IdnW5nv+D+R5ACPtFiB/i6W0L+yGHX1OYw3ipzKGzsSeOP/Ud64EXmjBXNW9ohx7UJb2C6216rq6aP44jHKF62ysnev+LiTT/9/93Gjf1vv236kb/isvu0Npxhtmy81Yb0OJx/OETd+EXDvTpBnzP68yE7tT8Ln4vsoEzE/E23RluM1/OI+Je4A5mIh90SMnI36yo5+hro82oL3BIWPf+Znfjl3fclx0PVWm327PwO+ADA83of1LUultl74/F6z2DEsL+TRB5bsdUQnY362qf7DCJsL6n08yEX0y2SvXCFGqT3bGUYfjfeLANBeJ4y3MkwcF4gdaUi3FwD45jiNJKce9yv608ber8hMQX79BfDrPRLj11/o+PXjwK9nAL8+AvhSLPEhlV+XDgC/jtVG5IUBkpqLuiTqWa1pyb4tc9YIWxUawf29ByI1YPuiXhFw4F6fJ4B+lmLAva3iljlLhS1ztgrmS1eI9co8D07m1qGe5v1ctX3ecS5R6HUxwKfhr4m4lWmvjdaMyNq1kfHxiclZjEmwOJmsuDNm4fLq7/xSXog4j/ov8oqjs9YIuNf34acar1hlQl6Race9QZR/XWHkFel+pt/cIEXDiFcP+ZD3lgPv5wPKOFdf6MP3ZsbOrhMdJ/HnOyXqR6EUlf67z0L/qWeh/9kKnR5zoJ5EdaRE+ld0o33fohuN0D/oRnHtIv07vo3+t45J/wePnSv914yrH82MjtaPMF/dU/kW3VNC3n1+j8q7O2OqX3TfZ4wG7+xH2rNQ2kPfywRSUH/XZyrtuSN4L3vl/SL6ZtAv88AXQaC5gtUY70hKLhH3UZq7BIbsBJorqEf/wfG00f6D3clIb5dgTifoRxlAc5dIGr01KvSWJFF6469V/AcrBtB/gLJmHuAp0luAHIY2dktIb9cdUemtSjR/WcP8vDBfTyX6VGYk0FqVeOVnKq211wNNDq4CWlP3mzZ8pe43XRHF86XRn4I+FtWn0gLz7gdYfxt/DB2r4Tf26fydY9BtWNFnVFyIfvEtuDAiB1T6RTlwN9BvQb15gJ0ZPr6e+PG37pPugDF1xBhOqHyu6ejYvGFXj8Ybdk6M5w0HP4/nDUMAY+G9Uv+BY4BnCTrBhE/OrhMcVc6jS9QH8pL/f6gPgL2j8YPgiD6wk5yDPoC20rj6QPA76QPN//7P9YHjqUE33evuYfIUa3/jOjadlBd+xh2hOTq4x4LxIHjWEP7GOsae0Hti7eTNDqxNjr60K/+tretMjvl6c5Jq+KGUZ3jU7Xd/NbYcyhyMx2dy5FzwuWZMebT8JOLcscXRyVysNe2oOIH0hxDvSpWxwXWMhbY7LkC8Y7Ie5H8U5X1OlOqwEsO9GSN43NUzNh6fPqyTcefF4/G8r+LxePFXKm0wnvTAoLxwSc/ZfY0HgN91JoPe8/T9yt5Utn3NiRoe7c/R+xXEW3pYs0nRD+McoTEtnnbCl2P7ZU59Ee+XOfqFai9N19lL6fYA6ObML/NjnV8mW/HL7KV2kjdF8cuUqH6ZHyt+mexRfpnktHi/zANfoJ10mOa7OLvj7STPF8xOCkxmdtKfP4y3k3K+YPsxCOPwIXlha9oKP8PdNrTpcpuAtzZNDoY9lQxnEV9/flAXX0TxddPVaxFfDz7jZjrUYdckBY5iEikZC3cfGIrHXcvB/5wXvwDj/owM+lEX4huuEZuGgnHrnzwccAe+jJfXCC99PDT37+Ex48NV+zLYFQ83I7ksWNk7Nn5fqINPQ2o8fi8+GI/fqw6yNvB91AGwjfc/1t5fnIbvMzmPcbUo6xm92fwavTHa8ERx/RgezD08/nxe/lfifH4cDIP8jB06O23Zhze5rcPMj2/6mOVvoU8h5WMt7kl9X+8nXxMZ29/QGo73N2wJj+3fD0w+d//+C4Zz9+9Hk+L9DTPDmr/hxMF4+BnD8XS08oN4+IWPjcYvbGfbwfHXwfZB4jpMDXZ+gecPuJwIf9yXf0uBKZ5P8aO49ti6JHdtcuehX79aljLDSAvDCi3MEecPBel6LQYauPND1AmK/acPsDYwprcjzM46wFxEr6m9HuMivaYKxzJTVv2DynNb/gVzU+xe+0eIYwxG//g4fm7zv4if2/ffj5/bzC80/KxPeLc5Ev/upIR30fZT312S8O6dCe++fyD+3Tzdu5d8PPZ6qOvaeCBxPVzB5QPa+x9+NP56/ujAaLoKfSov7AYd+hnlnnlKRWjje1qbj3w0/phSxmhz6hnt/QUJ75s/ix/TW+/Fv3/qU+3d9IR3Oz6Nf7cu4d3mTxHPm3IXH8A5uSMsbm2N1PiD7VKq8XxTqvfFSWrsde1+NW5tu4TPJN5fvl+NWxvrvsVUsh/j1tY4eHK/o+I9DXbe/dr4Sz+MH384Gg+7Pfvjx98R1fD3/IR3MU5B/+6vE949MKi9+25XQr9H4uG2KLHfI9q7TyS8uzHh3QsT3hXhXTUeEuMgMR4SYyExDhLjIdGPiXHLxz/4tufcNAZjNzy3B+gg+QPdfhbwjplH8DfzazR3ja3zhLridZ5AF479B2fZh8K2ul3s3HKFT0dtlPd7qL5jyuU9JoVPzwE+LSfw6emsll2KyqfZ7wldyKfzKCxL/xUPy/5/6WB5ZLV/T2c8LDuBl/2D4ry/r7xbzaWcruSgTqf9R88y9+6EuXd2nWUfbpI6f2eExVd5tflXsvl3JeP8H4L5T1Hm74T5v+Mca/7Hk+PnX07nX8Dm/0H8/PO6lPlPUvD/n/Hzn9qVOGcDHRs5Nvacw5/Fz7nrs7HnHAA9cb5SLxPnLCwslEzKnop+3WtpLPc7Tt5zgTLvnLOu+0YSP+87P9PWfdH78fPmP9PRLqz7u+/Ez9vyWaJ8zqftpL8/Du/te85f904i7/UE8Yw+dRx7DiTo23L8OEoT3s+RE+HP9n69h8eGf8nhePg7Dp/L3q83fu+3gcF+IzfW3u9DuWPBPmqIh33bIQ3n3n8vfs5bDsXzryX/iJ/zmkOJc36D4nnbe2PPufm9+Dk3vKffh1LnbKRzpjV9qiOS8Mo/fULfn/zC4Bk/w705EZaPyecKt3qkEVgEGCwOUFjcksvzk3X8xzQCC2Ew4hf6/uoXXjnkE6q/ljC3QQ8fcwJ8Tu1H+ORQ+Ly6Px4+Xft18AE787p98fDZQeUZg23V/vH1i9jfR+sC9mF8n+Gzc7z3AZ//POr9HwSFAQ2fY+/Gv187EM9PqxLeX67Er6MdMOGUNo+X3z3LOBS+NHfUOH4U7B/Q3l+Z8D4ZjH//xN7497vpu1ij1EXfn/vuOHAAu+XlvYn9XxDsP6P1f6IzQTcYil+HlQnvHxjCd5X1T3i360zC+ie8u+OMmodnSArG1QHU/88AfJ4fwVwnrJuENY5MHptkumSp2EmW0hpfSg6r/i8uny9wPsvnwzz9uV9mRTmQzZjr32nCuJkjfsyFVfP7QiZusMnkprn+bab2QY+JGxBmbBLLTVkDXpN7YLmpYqDSFBwQTJsHAqb2gW4TF6019Qw0mLIGm00Vgy2m4OAO0+ZBNb+v5+3hhNx/AebgC+95O97f0pr2MM2pmqDU724sjjxNc6mSu135I7KsLddCKlytaZdQPwXa1nQfGvRS81dP+4hp0wx69t9za3xoky7QwbsjKeDeB22bv3rTn9RzsBrzmo/O2lhNczA/XuU3f/Jjnyf0E+AD83qNxNzLN88VzTWTfN0Y+xi9SCyhNuNFwJa+dmA8wvKk+HgEkoT+9oucrWl7fMzffpHO3/6kEo9wsUTjEfi5ir/dNkDjEVxfi/TMeHaOhjuT2zZgIhty+dA8sRJ4Et9dIHr6D/rnJ4FNZyqwmpFPvXbEd+XfRvus9hH1jBje2Vhc2qhebz1LjNHGhBijtWeJMbIAz/UQLTbKRPf+26g9bqSyTBcD0B+B9Zk2yiYnNAbg8Jgyvy2Brx6H34BbYcC/XsC9XsC9XtQpAf96Af96Af96Af96EX8B/3oBb/sAB/sAd2lcF+BiH+BiH+BiH+BxH+K6iudx8URxe2cX2ZM59JG/5WM+8q3C6HiiD3LZftlvw5iPYOLQP/5LieUUjBVPlKT5xz1qPNHtNMbffAf6hliMP54R35rWS/dEsQ424gmNJ7oC6yXAP/WRz6Z5BMxHjnWWMY/gf8Rsz+0sngjawPwBbEfNWaDP0RyC22l9bRpPdHtA4i3KvGc8IeKemTpHjCc6mvzywyQ8V3zgTJD31B6i8W24r4U+hLkK3QqP5ftuBv4lXHa/2KL4v3POKP5qXdsIU4wBxT42yujzkm9nfrOjfvR59XRoNDqP1p+4SPGZfe1oGaL+ZZ/qM+sEXrvo7/E8FuNiJgxB+0ObeNWfYTFx62n9PlOFY6Ypq/6ZN9k7R8GOM3/ytCicfMuPsuARpe8XKA+XqV2pky9x8sNiUs5/3z2cUC9CtckLmfxLeN9+Jv79uQnvT9C9+/OEd0nCu6ffTJB9Q3r9ymbfOTg2jW8ZjKfxDYPxNM6b2uk+JdK6kepojN69Cr2XmHpiNAc0NB1x3JljwvNWi7zwieeN0XqjOUj3ghVoaJLdQzQbLxO+43PJ5Eun+izWUoE2I+Pp/Ddj3WVTeyRM5ftcetbPkj3q/IsBPhnxa/PYDN/7bySuDeg4VGefS+F74Z54+DbJ8e8/kfA+9s98QOz99zvG1vnV95e8MabOz/LsJ2v1dvpTihxJI/V2vI7utKWCvt5OQOYGauWsAZSZIdk9sEPuGcBawFh7B2V4g1wBMvl3YpMcHGiWNw9gjv2wTPJa5PaBlmHiVev16Ov03M9liapM/v5fE2XyClG4rBLksh941Q3SVWPeXwlr6Q8LC3Ol8/+q+or9cP1n4ltfDjM8NFjy3whXw1yqC2W52rXFUF3Nl7hozShi8BZaENfobzxvy1vIkc2FSLMWwrm2TKyu7iBn1u8j+fUc6SrA/ZIm8iTI+rv9yWDTCK/s9iHfmPSGFmt4Mxdwe8iuXvNHq3x8w3XiC6AbyfJJaLMpTxj8zI91MPCdQ7vVfet7RS8XHInJxbNXFyyoqz3zlrZuPK3RIrs8mYLYQp4ZMA8s9ZlA7nga5kkh8mTuDpIfi9v/x/xr1DfQ/mnT2tmB5w1Hj/jNl26gZxzRM7U+esjHN18r3gk8liNCAcK3mTxEa43GXtfmZZZRBi3xNZGTo+r3LXo7wf+k1H/EGGo8j2xRe4L/aRjzTZJ8wtPLfO+3xcdpevAs5iabOI9DX7HX0YX8763hUeezoP6v8loT8PIXyCa+jdy1fjfJX+9Wxs3OmS7y7iDSIMINYYbw0sPnur9qY7Pr4HMUxqh/7nzdcwflAH/Xt4xpI4wpUzemF3ex59fQM5lxLyMr3K3UlwTa6gXa6gW66gU66gUa6gUa6gXa6QU661XrxWANStQjxqobg7TqKZkn4TxDZD3GnvswrxNxI/KRQgvQb62e/k06+ueKYB5J9gPJQR7pHekYaRfxAWlVraeFerdK90jLtLZWLCuq0vEjr7F5JoGuRWsFYB3uy1aJ+5Jr3HOP62nSDzQpA03KQJMy0GShaDUE3YweC8XjHNaX/0leAPS5rieXOl7cqcEfcztVPnDhayod+cQSGLs3pcJBjIHCu17T8Ap5ckdKcDXm4CfDOAIpmEewsXp/6Ub/upMb/TimUGh6Heqn3SnuGPL6NYqcCShybBX8rk1FGwLXunT16+/edTtHJBfwlWqU27/erY2DXFTjDmfuqn499Y7bs8OY18A7r+8sk5Zdf1815p+irM+OFEhYbzGF8zrmKjIU8exTZdzQVx/Ge+I1b3LQoeIPnQ/HxkJzsji+EPMIZbnbMZ20AQ9ndIdr/aPXVBydYcfzz7pT1NqAbE6ZutpMy1O1vADLglJWOxDuN+D9MWpMOlLZ+Sm4Dp0p7euQBjoB9gdSsurb/6KLr08J8h+kZG2+hNhWWkf6KMIaRRFRZvSJ62wh3YW4zrje2vsz7JnAS+yJ58UbugtVPDl4JsC3JcQrC8kYc2dxkoCtYlZy2RJSkkFrCoWS6flL9t3DQb4bcADjFTcA7+WhLbA/86ypWQOO1IqB+cRWsYcj+Tmp7gFvKjd4dLWtanlq1mBmKuocXpewcK7U9MuItzy1ZwDXAetR+99MryhJ3UzjKxjeXw06b51PWHiDpI5tx2rQVXC9Qs9CG9dJ+vPntVpZ6bQWj2diDa+uQ5sB7K2uXDFsAP0Kxh1K5iIevlTqT86K8dFsEc9KojUQB2N+zOeLspppLmx37PVDuwB0hY6oiDXchNc+9fUnM1/CgeQaPus13Z4v0OEGaM98aaafb3OKL4CuTmEXVx/4utXmN2yS+Y1qP9yL4R7xBi7A4A0wBv3dDbCLAHx7Aaa9AONegFUvwK8X4NsHsO1DfNfXQ2pZ/clqtNe2KDYYo890aLeGb0pldcuRdyKvRD6JvFHli4m1tJDf6uuTIf0Dvrr0PGBIlz+DPATx8JL/U+AA/ARxuQt01B2DWJfBN6KHPPEnVe/4hbjo2Pj8beZgkJ8PunXWX+Pl5by07CXUZiCPzsG6Fw3Dm9wbuSfds3A/FXjiJPbJX3+zzYe5m2x9HXZchzUUrxk+IK6Y6NlR163G9cc1wbXANVlFz+bCPAmn30uyYvp4g/rXz+KfUuo3T9qRoONDvzOH9fkXah1Axs8qlPbKFfl7Nh4Cdog7lJwVwfF1n4nP50Be0gnXP4+osgvroFSJ84EW4Do9m2Y5PT+d0Q7WAwon8S5830KKq837nf5LFDhjW1uVdvDdygvK/CTUCPbnHX6wkfNJw1M+bA/PZjWSJ/imX15asVN+hh8ZD/fjwlpdPq1pttexS5njcbiO9graamirIGwT9aO5u+Lhm3NGB1+woV7+Uzx8TWfi+dk9WBMX8OLbaEhPN3nGeLoZMtbwSGNIO9x3oB0Gzxr3gzvj54A+MXoGKYnPJ0Pefrb1njDAat6jfJJe0eScaSiBfyv1g5D30v33/1NlqyCuAn7Q81r8WLAOLo6Fh0+ExcYEecAp/HjfEMPH/uQKR/4r+vo6gjgV6GhYno516xym1PZY/5M2J8bO4nlwi17VnrUCXMtT3MFMwCNrCsahZdjNRbaRs7HwjKD9i2z03KOWZA0/t4DesYdDOcPnW1K5Af+btoqmX5ZVhJMsrijITOy7P8VdT35rc5LUrNgyHX2ea38z04N85QU2v3lvpt9c5vT3p2De0iXiBIK6vSW/6ZfOimgKy2WKGlHXmlF9WoElwsT2R12e3ENvSj9q1eYtyrinADbXwhxplP7/l/j1wHP95CQFv1cn+VT4YS0sxG88FxmvD8G8lyhrC9+DeFayWWb7dub9bj9JDYa9pALayW286o8ajZxPljqOIz2MeQYHrT9YZ4FxpANPRd/lBIJ+mKUOUIQWqnw7XxnTvUtWCE3QVpvCzxB/VP3koFof4AzaK3U+lPeoB+B+Fsp1T9ufRfPeZ0S05z7Xjc+DZ6xd6qTy8qBSv3PHasNqQmPZA7x5b7Wf73SJLanBEX1MT8fLEvLd0H/5+Y54P8OEFMT5DHsz4NW8tLIlE+B7GL7r29mA+F5iFddEQTeojmAeyErMVdLrJaiTaLrIWPoIqyHLRzV9xMQxfYSeEQU2bXcKy8VGOHzaqsVj14I9xc7ZuZDO3UrY3FEvGNG/QDc4+s1oesUcc+Sl1P/1f/H4tVPW8U+wl1e+HM8/E+n/5YT3AzLjF4KMsLMB7IB3JKMsYuP6Vj6LZ5qeCqIO3rcYxn42fncQ8MqonLGkyrPLj8TLswaiyTNBJ89wLxFpFvTQwqZf2ir8b2YuRT0TZZwq35w7NPn21icJ8q3tu8k3B+A/8L0Ift94Wl6I/OCSl+J5JPrIVB6JPEzjkTnSVS06+yTt3Hlks45HbtTxSJU/oq5N+wS+KNx6C50/8vLFgBfn2sf8ZOSLpX7zfuSLd4Dsv1THE3MrSG2maElGflhc/emfNH54yYvxecOl/6vNcc0IP7x2FD90v5rgM9Xzw6eX+twtGo2M8EO4Dvy6foHCR/oVfjhV5Yd7s/xC9VGJ8UNn4+UvxvPDU8Na/ZVz4n8tGv/bAe926fS5b9NnKlrj59fwTbw+0/NiPD0KQAPJsCb9KRXRDPYctRdxLsuIu77+BQ2ulSDf+6l9oZwpNMBotXUA5wG6KejgqH+p/HvjAMuVukr5vRZrncNanVHmt1s5R0+vn7Yrsr//axZvqPIatT578JUEn+pAPL/hEuaXA33imLYpcLHQ2KyHRbW9uQnttXE6fMD9i5fGwAe4jvhwXUs8Pqz5RsMHWptUwQfy2zWO9D/E40Q5PGseJSPPDT8uf0nDDxO0k6PwsS7gNV3Ax5Yc1vMxQRwCuutKcauxSxGsg874mc1+MAl5GZ+PtI00jbSNNivKII2fZfpXKHDCPk4fYu13qfxsR4PGzzoYPzONxc8SZCnyM/OX8kL064gnGI8D3tWL11v7tb2Ks/HwFpB7DjzPT3nHFGNxq88o8Dml8MrPm+NijWmtUDyTD3n8BCoDb4gsl/FMQcY/0deg8c+50ufbNRo4ZTh3/qmM34mwrDUEeb1/RzAwfop+DIQ/+jZUvqr6KjTeeiusBaF+ifLvwFtzDMhb0/3mN34kmcsy/biupCFT4a8ouzKXktAlopH69pKqH3lZ469//r2Ovz42wxfZpsEgQPnrwyKV//8bTz8vJNDPie1aziWjn3KVfmJR0KlPKPwFvgMNlUszce8vhZ17K/xhiw9pyFyWBby1tPGt38fTUJTy1W+nF3X9kF52wztH9fWvgLc/qIwBz45uTaui87okYV5biG5eYHdfsn0MvRmuI1+4/IV4vhCKanqzxhdyKV848Xz8nJZFz21Ol+jmlAPvYEw/9r9Z4TNT4Xcire3ukxei7oT4LgwxWlmpPP/CGXZPr1fhc54hxi8RJikvjQMTaCtlm2YLJvJKlf+pMNk5xM49ML/B6WBSTmFyaGs8TEJDKkzqrk7HGHuyyc3OiI6Hido/wuROeEdU5vhrBVYl8Bv1wvm9iftsCfEvvWevZ417Zehjxz7xjM2Rcy0uk9Bf50JfPO7F4X4b7sXh3hvWsUafPfrjcf8Nffe4R4d7bqqv3v2l5qc/9NxYMTD+8FvPqf77y+24JiLGfsB1hF8DwM2SsoLWvF6cqtW/LoHvjVcQUa1/PVbt653fWuu5GP5nSh6PTWK1iwuWJJ4jgDEknBpDQmsaXzHnVVXmJWNsrxaLw+Jw2mgNIy0W5/UZGDegxuL8WUcXE5ID7raRWJxDSizOrmoah9Nb7YuXn4t7jWReL998jWh+9BpfpxKPU5sQj9OcEI/Df6d4nGuUeBzMX7PReBwaf9MwTwxg/E0Y428O+Tco8TcWJf5m63P//x1/M/Qd4m9MSfH773nwu82Evl+si8FqKqn7Zkg//8neGdZZio/BKfLytUqsyGPX6eJvdivxN2sEc9ma0fE3s9T81IvsXhp/88g48Tep48Tf/EsXf3Pl2PE317P4m/BZ42/+pYu/ufLc4290eXH98pq4+Ju4HEQFn2rnbxt44Mw6JXeuKGJJ2vawEscNa2rLJxlY5z/bTs88KCnxsTiysoGjybc8TEKgO2Att9BBEePj1Fiee59V/Onr7/SZlPMkhGv3il4lnqd/aKz8U4A5jedZ47h5jHieSTpe/0JCPE9lQjxPCNoP/n50PE/HYI27aZx4nn/8jr3ThPE8vVo8z6tb2PU7dfE8Wb8fP55nc9PoeJ59Q1pMTs/z8e8fHIp/vyLh/Z26d7cmvNuS8O6VCe+GRupQPzdm3ox9pB702PcnjNSDfm7MvJrjMTWvZqkjvUnL9xuKxccRJZ8ljuj4QDyvOjgQn/fqYHFCXsx/NYY+ofteFpM7hnVnc0ztMd7EDTC6bHOaaP6BBf49kZGc2Moy4AGTlfihubl8ySSFb3mUHAmWEwttRaCt3m+LH4LxRBw0fucWGj904dZxcGF9se+JTYm4cLUSP3QNi//ZMk78ELy/JOF97H9HTHv/iS3jxA/B+xduOmv8UJI+fqilh50Prsb5oN6ijxNQdRjUXdSzwWWZ5HkLiRfjgPT5t7VJyjkkYDsJMxpED5UrGv9M5vas1p/dS8hQH+p2Fu6vq42cv8/E3dNn5X4H/OvyOcbZW6snkHXuB5V5JnOFwfizFK8QTVSG5UWalf1ojhx+qJ/Wgb/ELlIbU6D6j2edpv8cMGj6T4fh2/WfPMO56D9H/R6PTOXkKcqnXPaDXA2Ng8AayM2/Xep4S1kPeu29+f4OuPayci1kWOf28j0uL563c3K3H+eONG0hO6sfVPSCM/IbecKRNX6MDeG/epvSPOpIVym01zBMgC9eDqDJyvfi2Vigt6AOKMu7XJW8G2y/bdXoT2HnYgZc6OMwkt4w77BSfmwMRKImUuYsIXzR0Vl18Gxv2FyGMRC2fGMgPcLzs8VOGmv0tgP1Iny2Ne2giM+qzxGl3zaZFOE8OTLk6od5cuT1wreeUfNFIw/huSckcMhlbKh2Ia0ayeuAp5vCyHdNcL1RebbqyO/883X1wPXP4f6sBfSPB5Vn++VN4aj8Or33o2fU+An5hn3U9/mTPIz3zWxY6sh/VqWLrDDG+6r6iF7fOOv5TrozlRHnM7kVfVOH0TfA1rQJ5npooyJP5PH57wtnxue/a8+Mz38fOKPx37qntBg6kcrerDDG5f+n80Nc8/IVFM9Mip2hrh/OFdf09NNKXu+wjq+Mdf7PIcZfkH/gmJB/tMtZUTyj84TGo0bOCj6b7fAU6r/w/q5GpaYsyXJ0px2pxvklnL/FbDdQ4rD/zoOj+39Z6X+lrn/hsmWiGlsznVSEc0gweslX8kL4ZLGJM1aLbqVvD2G5DuP1PTL/cfo/8cz4/ds+iu+/veG799/58Tjz/5b+t72fMP//oH/POP2f2Dh+/43/SJj/b/+D+X/E+kdZpo4BZZwqy+bCWCoJceA5UuiruCtuTCIdUyfw8h1k86CXbF6NPHZ5co27FWyFNtI+OCy/URgg7QPIZ/EsJ2vDYVct6RloIu7Bkmm7qi0pe6obSNZgiHCD5kt3+fE8J/TdNZOKQW+DzYlnxGCsHV4rx98Lb6Dfc+j3XPqdp9+d9LuHfndIwNBKOHJP3VqZngOGtiJvgN/4Hc8pF95b4Bf+PtOPfu9SZd34rnyxm56/NNhHSGHde7KN6VXUX1JY9zvlt4m2VcjOqIa5W1Ii1SgveS7A53HK2VBfM7s08WyofaPkpRXkpQ3kJZ5dm62cDeWjZ0Ohv3AClZc4llI6DzvYA+r3EB3XPXX1yhwDujnieY1oKzy4UZubFXg9rEUvwL8X4N0HcO+DdegDWPfBWvXBGvYhD8F4z58/oezBAS41yYTik77m71hnhqvjsnJsXOuVcWVy2rhgPrzwypu+9xX+uFbvT8S9VpDbH27Q1cFXbGcWT1eTR2PqGtY4PI1LHfVPqjz32Tz1Xk7DVgcP971wf+XIfXavHK4LcP1HCde9cL0WrrsTri+H6w1w3ZZwPQTXm+H6pITrJY1rHDvgekyB3Xiw3gDzVuHlUNaxUYGXVbeOeCYXG8tSx2ZFjpUr9mPi+0+N834I3q9Q3s8ceZ/hs/EMw+8G5Xd0SMPv40Ps/RKYV5byfteQep4O72y8rVBsvO31UefhTKXy++z3h4ZQfp/9/sEhlN+b6Dk+e9YpOkxCPA3DBZDvqsw7o5O1GUy+9b/P+Juqo3OkjfLYIPA1HvjZr3+r52faWWMgP4P4LNoODhKk56tVrFPXFWXrm1S2jne+5XLgieXAx1RfJPBPsBGWhp2/UfURH/VNCifxrPkZdVdBX1Mp7cygsMd4BPXswQW/VfellubtoGeezoiwHAE8f5G9m6x7N0q0d9N17zYp72IOpwXeV8e29XEVDlfA/FlsB57Ph2cbTCDsjC5hYb7EzlEsovWB8NxLK8wvh1SE5hE8Qy2bxjC3pm3zs7PVs2keMPa1htaRPuIHeIBNE+xbTnlNm+v8+nOFaZFXHeuP1qnwE2mexMj8ZS1++rqRZ6rFTMX+yaRnX9ok4da7JHp2J4WdLj4LfajIg4D/nf6NZh/mYPx8eIZkvvSwH2HgwPOgdc/u0T3bJQf4S54cHUPvADtO9bk0wPunhjfxyQBDuL4+D2B3rwJ/UR/HnjJaX7S8d3Z9oX3D+PqC80S8vlD/m++uLzTtH60v4Bg2wxisMIb8DaP1g+MJemvXWfyzbQn+2Zaz+WdJVgzj1nNAhwD4DaowKgF684DOYQr9xGWke4e5kuq3Jfo6RorPNkASfbauOJ8ttN8H7fdBu33Qblwc4tERHwj7vYb+ZrLTqaylV6eDx8lLJf4Q/Wb6eNWe9WfxmSjxBxW/TvSZ3EHrJGj1FuLbq09ozyvHtzcpoT1eTqzfEN+eO6E9ktBe+9qEeNphHS6nMn7s7dTwF3ky4k69gr/cutG8GG0coNXVeE5ojsKHkS+/r/RVSXH3Tf9YfKMEcMMDPErlCeVkM+W/f65L3CMSKR/OUughGfrKANrMJP/uQ3pHHsLGUYg4VEevYX2vx7T54n28dujXWs7D3N9ouROYd1GQ+vztI2d2k/boynrGl+E7PP83en6ncq43PV+2NW21fzk9x3Z7+Kpt7FmYE+BisA/m0ofyA+Gx57FvhwWun/7dHcOJfIbRd9s7Z+cvFaHR/GWq3h4Lysp8NB5z1WPnzmOwf36c/nt+M37/H/7v8Kj+X3z0u/Xf9o/R+OmG/pdD/9BO9K7fjI2jy0FfSMG9HLrv2eai+adK323jrouufjPga5MOX5sVfE3/VSK+ShRfV65Va98WKrwW27HVIX6hzJ30G1Xuz8jPDNpGckLDXE3c+fEFqb7bMU6o53H2vHDybT9R9njo+afkubxKUhFF/9rywFaYy3Nwf2u48Xl9rIxPDID+UUncES/lldn5hJTlCwGbs5LicF2YIwXwWRbhLTYRZTCLc59px7PE6ZmslgAdNx0DrCeO7fvqmGBNkSboODDWmrZ5/+D5a1Uau5+2eSCpxl1Jz9i25Veyc+RjaIfNnLaH1h/ILr1LwnZP/3p45LxoUxDbKqP16TZS2DyXh9c7Apir/SZ8PwI6Fz7zSGB54G1Ha+CYA2mSnQH9NnweC3TS+8l2uB41kUdh3fZGZ5Le0Eaqw6HulCepc8P+f670j/Hg7Mzr5/KMsEadFL5vwrW6iJU8st5O7l3/fFKdlJUc+AH1YwINA46AHcHov0GXX6C/F4DrIZCPAsALdZBKmhvhD2NNe5SLSzT+GRGIm9YdJWRF9AUD+mVr8gLEHRPgnX6waRDmnz6uPs9qlNLzeMmbq+G5CAf88qgi4+F+DOf3xFo2P/Y870T/H86T6rwwT6E4CWuY1v96RO+8O7+NwhDHcX90B6wDjL+vPC5/At4HeLXR89cZjMaDjZhgL2yZWCfgvhmuw0baLjvDuwX6fYHiCuKALSjceiddq8WJ+Vmkl/oxAcdjpuAxB5vD39bv+bUKGzfAMkuBZS+sJ+LJT6MNFKey89Fe6YR+rE8tBV6yZ/3La0b2tOm8M/X5f6tV/XW5qMCxHnUZhK3zseGFcbFvoU/ovviloWebMkOGkbPJk2Fe9hvbRHg32EnnN9uOc8wh29ZPJen188iKp68j2xquJ3taop4SqXLYKDn4MtCNS+txfYsX/O2xeeSw3/fh4ds5cvi/VNz986MaX+mg7e5Zj2v1gpJrVBIoiiDOEHK4MDOI+lR2BGVmcK1mL5On8Ozxe0WkZdujKhx84UM1Gl4SUhDDdvXrumUg/nz5kgDqlHv6rtS13dGotA0y+B+KrE9s584B/VizYgIdLxvnh4+NPc5gnX5sK8Jza/Q0hHiePmq80Vi8DjTK//u3cfx/tePLuxVbR8u7Xau/m7zrfHsc/+e39F/12uj+879j/55x+j/xq3j/dybV+YGf7VD7rQijzr2nRuvz23zeifDvfGuc+f9q/PnHBseYf813nP84/Z/45fj9/+jwGOsf/I7rv3uc+X9L/7bTY8z/O/bvGaf/E498i75nG61v7gp8x/m/ObZ/qH04KxqGMTz4yGh9j4CMDIO+NywX5Vu44KDjqTInygyO5o/hvir6V/JGZH3dIyq/fLMwOYD8sCAoy+n2xLxl9KOrecsbdL6f0kc0/00z898EC0n2SqzPD9/rQb6gLyEfY8ExpxflPdyrYHGBWbF0n+ZPfYDG8GRtzsSzMrn4/i3c2Ha5kYu3y6NnscuboC9RqU9o4tyDmVzFoJXDPGLUfZjvyETtcqYHaTY6s83n6c40GspA2zzPyXvSRXwfa5skk3zFB8WePwDjgX76oJ8+6KdPX79743kJ56oRrX531Zp4O9aq2NlNRKn/JiXa2YxfwFr3qbr9EgWmPPctuj3HDRq5rEFcRz1Mfr5ap3/+v5RdfXBUVZa/nU5IJ8IY3DiCAnY2oB2qdWMVut0kgW5AaQLMdBbEYEA6JGgioAFlfJH36G7EMcxCVWewZtMS3M6OmQUL3Fgbt5gqrEoGGcGNVTjlVEEtayWKS5J2qsKKO/nuPefe+/re9zpf/kGF27/33v0459x7zrnnnkv1nqWU7l00F3VVMeoEdkrr7KiNzn8X43Zi7cN9jhzMybAec9ExP56DlpdrTvrXRcd2gOthc3g9UO67Cv3TdQPUZ2N07XY4Ub8l5LMRvMdax7ENqOfqulENbcu/nlDy3wIZKD0BbYV/VSNnob1dXR3FXV32ks+7/hjo6sK74R+qx/G6p9CnZRGHA+8T+UNvaX02WbrQ70H/m08rBN5NJB6O3qD3jzys3rGFPX5XtZpI5Lt/QgocA1BO66lVUMYsxLHPfqbUDfwM71xxRbfENLwbcCCx1j3betizavCh+t9Zr4AMvw+YHWyjy67uRKk7+ihRd9+VlxNda1d3W0mOndjc0b8n6rUEWYVxUR5fvopxCH5Xn6oU9ap4t0HuP3i1ROLyMbwTJUA+a7oA8oKYhawDnbNUGwcMn9HxZo6ncXzMhKsct3J81IRv43g6x0dMeDHHMzg+bMIXcHwWx4dM+ChheCbHB034DY7bOP5XE36B41kc/z9z/zmezfEfzP3n+F0cv2PuP8dnc/x7c/85Pofj/2vuP+DAL+7bibVH0berx7sz/1WVmnv/bpXZuvlRpaJaQ//cAKkc2pi0XRc6odx3k85pTLZBZuMgs3F9bkG5x/ml8vUZyry0P+EBXf+KIuYTzBei6/iPvSZiWo9Fvg6B/hvBHF/En6n2DrEzlHT+D+ptxVybqNdTu7bxkyGjfRLdQqCvDzkHgPdB53cjz0d3ELV7FObJMYzD+JdiO/ndQey//+1Wlwd9CRVVWi1fM3EcWCwIzIXQbhyv4/V6G1c4cf7AZ5T8BvWOFeW+m8v9LS73D9fL7bnH9RzI/woHxmYm5X8A5f85Lv8OLv8O9UYGyL9HyP+XGbL8P0zlH2VfqXhBQ/kfSPjc/gll/1Oj7K/UZf+WyyD78wrUbpR9T5amrM7UhOx/egznI+StDpQtwITsf8p5j+ExjgvZN+IhjgvZN+IBjgvZN+IejgvZN+J2jgvZN+KE40L2jXg3YbiQfSPewXEh+6b+c1zIvqn/HBeyb+o/x4Xsm/rPcSH7pv4nZd9nkn3df22UfxqHBDyN/N0G/P3hL0TMTgeU8w4IOb0p2eJHXxH6E+6FeeYtVBenhTz6vi9+bwDsxG74xnb+zfYRdq6Mnc/Dc3p4xxfa+R53jLQMngZdCfW0GOhobaQzcp70DHbAmn2ZeBu7SF7j3oqEwbdWM3LYA+/0xUhnHJ6jekAb6KCoB5xH+xP0gMu0vFzron9d2qDp/DHGS+EaCjrhh3fA/rXC9LJM2j8wzh89Ln3+aIb5A+N02ft5H57n+S+wXwHS4kJ9BnWnRy0BV8lBfaxojuoipq/RO4s9AdL5BtvrZPPavteFHyMU+UMvm9/0uRB1kIec+ly3meqqmVT3tpC+utHEU27qV4O1AfM4YCw1IX8MkcJF6mZ2xtjtcWWpd+D/OwdtMEdkgZ5kjFdPJ7Yw1aE9i+g38P+fEM+qdPJZKJ1ku9OJz43fu8ZjEAZJT2QAaINt/6he16u8Yfg9JM/LuFYUD+N8K/jjGuePklfZ+LwNczfSAuffwBDjFVr+q8i7/0X9xPtBup5a9krqflDXHUbPhgi7byOX9ivLgfkssF2R7xPr8W/zkPG57xL4XKaD5oricfHoW8E+tGe2Bv3vYNx8ba+miDULx+GcImiIdGN6eHIswsvwXCH0kfni7O63pXsebiumGN07xv7t22+K0b3D2t47KPlUkjF1zJ4n/5Hqvy/j/vuW11JtuQ0W5rtH283D89Vhv/782sQ222gaxmPuoOMy+A7GzT5V33H3Q84jNG62Qem42+FUMG52ixw32+0yx82uscpxQBmw7mW4FYdNu2O1abmrMrUPPJ8EP/Bka37PV9Qe+pLbXMciaWFcq2BNdfj5uUg9lxfaxtX3+erRP/n+qlr1+ju6D9bbF7OQEt3WQxsPrK/KP3lZjG4I7L3T/D6gc9J9QKgL7d3Hxqxt2j0MjC9m+pN7Ru+sCuC4UR/bySOuXGn8bDMYvyOGOKpZMH6z3EqhPH6ldAz9fjZ+uRbpjl7420RaqE1WB/KsoK9703at54A+XngPXlVxGbV5rDRvVQ2NFc5ytmc6NCX+ftDG6MHOgQAWs3QX4zdI4FbgT25sQ6lGVmeH8d06K6u7js8d9QeSMuNmda0uKaM2YHYUaROzeEpwPSOB0ko8j5pbWpKkUSJhpBH0I36Mz8ch0jmoYH82rdaQBxpfNvilwyHcZ4S1pG0sOX8X+ceN/lQ9r87VscPe98ZS421Qnx3aK+RStYh1snLPRPpsrUp8mWrXqNBn618V/WfrxGrqq4b+N74n5SNi/chrvPJS0s8axvYXjuvxR92u6Ir3teiK1Pjg90Yx/mhy/AiNP5oMt+dUA66Pp34/ylnTfsBU9VePTV3/mrGp6188Ju5lwTG4tNc4Bs4xdv4f199qvvZ2JtcDjHnIx/zWdM3Vx93yyszX23bC1tsN49OstwOzDOutOpP1dsCWXG83mNdb+J6+3iqw3uoy8+R+IZsKXW91nlnaGEvyM6wvY3hnJMxvq0vdDj8BebG5HykjhjvOcA5AWd0zKq0jVr7/+2+T+AO5T3L7vtQ15ALf+8J2nton9kbK6Fhyfx5hfp107r/DuYTNIWwfVr/HawOdSwiXf5yjUf5xLllKz9o4eewM658d+lcA/bMb+yfJM43/SrYJ69Lntfyobu8e3S3HjE8ag8XGKc243kY+mNp/+kjdBPvlsIaiztjL44UHYd1FHxn6UvW5ZIB0DoNeNZxIhIrQh4Z+M9wLH3uBfS8N3qPxDw/Uq7007i3kmgPdHeNz3jFrbO5V6G8bzDEdnM+jP2/R8Hwcjkl0bYsWfaZF+8vL0l5aZKekuxRQGuVy2h5DPcmfpTZbQklaf/iyoDXzpZ2B90ucbVRXRT9akRP9bEr8TBDPiyhFg6ozDffVKmhspj0Nn7OW4LPnScuJtpDNfZby9CInrBth3KtrIxaQRW/j4vQw+jpHEol5brs1+2BuqQPsxtISu7WgXtlUruXSc4nwbnaBe/GDpfV4NlFZ/VNtqb8CbFsHrMEdRUt9GPPXUqSsvh/+eof8vlKQUe+QiL+9RPOT0fvLakTuAUdGyFs2cCWYW/pxEOOiwN4Io2/kpsUo33hXN9Kg/iXdn9DZDzTsn8ifgs+jLqfrDBm10/tWcqR4xR92iRjAdL4eyOsmtgnXTqRTbunBYMZLE9OqfJzFt9pOgv33gjHOonGXzrtAR1IZqctA2hUxeU5n76Ed2fe88b2tu0QsZTvQ1U5qlTZ4H22ys1ZGRxxDnQ+c0IY2sCOcpvkS3wf6n0DeUC7agsrF7KA9jb2PuSrwXl6kK9IU6ekAmxLvLGQ+dSM9l7wg6DloMdIzkXABTy06iPTBWHtsWzp5roTyVekTGskudyOfIV9RPiMLnMhnyFvsDGyRdpXz0zX4a5f06ON7xLijvNq4XUD8C9Q2qpNdXNmeeTLYxHVs1MMHLGxsPUCT47ukeyUkmxzH4HaVfmZKj4s5qGLM1PwaOT/s62rNGJPhCyR8AmztIhZ/FSq6vZu1rT1To7EJESb3ff6r67QOGMvLSdng/I33XWDMZ/y3wT9L7fKlwXh2vxHE+FD9rDfW0bhb9J19e90IHWMuJ2V83kX+N8sKzs2y7/HbXdPLB12brdn1uObh3IDyjzQs5vIR3p0al9otxaWizlc8yuJSu0neiZuw9n7Ox7id5s4/GbTTPYSjJ/Ac2e1dwi+CceYukpqf9pq0NoZfZOORxv2YTVzXKIS+tuG8pPMrfPtAteBXmr+a8yvmIJGf2yg9h/mrT72Y2ke71EfMX61YWB+hLycWQx/7dvIYZFP8o91apeD6mg7zsy4XOJ7fUb1hBebzcut98GP+0xenHt/Y8GHvjWHj+O7ldR8Bu7induq2h4A+zcN62ytp2x/h71ePsXN2dpCZrTuN89GVgDh/TM9IwDNgmzU+ZnquxfQczm3t8FyW6bkhaX7D/BqFI2Gv3fqigr5bynfSWHVI+Wd1vt9aM/H6oPN775DIn4xtOFppqn+HPL9WnsC67KSGzbEYB7Z6nnZjGPMX+NxIQ2XTFo3SENpTOCLpfNmp8QAdran+AzwDFcL4xxcmPisAdsIbY4kV7jSS5aD7FTxGVR/fqzM8L4BnqPQ+oq4zd4dODxbvp8e5+6Q4/2JpnxjXL32fuIbH+WPcrMuCuU6Yz8J/UvgsBizC5r5pmd7mbkubzmdRrTKfBTu7hPvJuo0fgHr9ko2/ZgY2fswyExu/OnlWSlm/WMPYRB89bxRzzd0p1gGMJcfzTdWSvauPdUGV4Pur8nkk/j1cXy5Vim+dxznkgWoqIwrIki4fSPfz/FzD44Hpaa9/H/2Du6TvlyfwDMWVIM49ix9cUb90YAes56VUV8D5C/dxlAeeV+tOttJcc3Y8v8F1kKUDQRXP6e3lMWJ7JP9uDOzZJox1Ars6Amvbvh3J2Ki+JuZb7vVJ/cd+fx4Q7dqTYGNoH5ve/vaNT23/Osantn9t48L+jUCbLz2ntzWvL3dcv08b+5E3dEbCBqV4wana55rGPp83jX0+ONrk0cfT5B8w2JN1LWw+wXxGE52vnAtzix/olVElzy37k7Eu3aQTzzS8ge9loCyTMP4WxxwGX2zX51ER94Rn8zBvjPlsXg3pGYL2DovY4p5h0C3Bnuhe3kG8I9dg7qkjlmGF5A03kMrhCAkPN5GWYZhbRy6TypGr/OyS9qw5FvllmJv29+4y/c7yXu3v3Zjyuwa8v7/38ZTfFdUBvy/kv8+ia8svVJX6zu571E7ylrdnfg/y8l+H0un97qsCi0kEeEScT2jZacoZQefJGOh6YReehWzZbvQnhyx4l2N3kfKPKw7R3Myo252sOlQvPecEXRl9xOz+jK+C6JuAtvSl6f0HXdAHPNDK33GQHhrP6SGdLjwj5IO6PRizDDp4yzbpznILy1vukvIz9lRO7O938fyMlRWmfNq87Yb80tgH0Iser5jo/o+vgl36/R/8uTkVpvs/KlN1kEKT/tQw/i7IRuevl5Hwr89tFfd/5FWm5pc5DfU1kHehrSsdOfTuzEQ+ISudF8bDXuRh4Ms+4Lt+4Lt+4Dt67xjwXj/wXj/waz/waT/waRz4MA58GgdejAMvxoFf4ygHnz87cxnQc9wUkh56Bzf2C8+t9ZXzXM1j9A6TYjef8+w05jzmovk6gH6dFbrvQdD+XEWS7nHaL6rvxpZbQEH0D/4Q9IRWgv6KeSG6V5rzjd7eYcrfi2d2kTZ4Lhnz/z2r67YqzQmHd0Qp/7kyqHzzLt0/+dD0Pu7xUN0Y76eBtj22Vcd/+3dfJppBh74YnA20yL0/AXwc9mKbc7/+6JDn9Ep1M5Qxd1hJudAnC0Eedfk0y9+BLdwuyMR8ZPc9+uqodPZyrjhPUtcs9Ck5tu/e55J5n/uoj5gsdQboGRsv2IDZzs00jq4qWX8h7pfyOgtp/K0Vnudnrtbna5fKp4sBxfU8X8N5NDrts2L9Y3NTlXppq8ghkfT/bNfjH7E9q8HGQ99N/wi2aY98jk86Pxc4OXm8o2X7NPGOT6fGO37+zI+Ld+x+J7X+fXx/LLwtlSY+eraF0QT0Ci+LsdsZQtsH5yaMnUZ9IwD6BI7Tx1tETDTqDK9SeWA0ynsmuU5POO4yvfG7czeLb+n1YV1YD9aHz2w01fc2t7/1fc0jCX6vWgj9q/1xbZsuw1W9X2zT9/+/Lk6eIb+3w4Ux96GTt+iZtibQsU6fxL3P7qJwhaircBL6hqJGfi/jtsOSitSxvUBtBza2bcDvEVgn6BkB0ClP8ZjPCOd11PeA36nuhzof6j2R37RS3e/MNqH/BKh93l1kI7W9tWHxDRz/lqfFvtxE419ZIcbmowqd35me2w1tqtwk6tFlaeM03zTzX6DJOD7Ie9jmjGdTx6cOxifAx6faNB8g7W+XsXfuht+y0pmcjm2ReeYbynfLSCLYulnw3qHriWcmaqvep/rNU/PpVPHkoX8y9q+S92/J1tT+5fD+pUH/ltFzY0xOhvg4xyaXaZ7vxzgePX7Rd7o/ffII5eUcsq7PnvEk2HxLnF3U5nsLbLCHnR0pNl9Hig22wbBPbQUb7BuXMu+Wesd6S81d/j/qB66bwQ9c/arfxfI7naU23xJq89maj7guSPW1zaC+Yz+yvmapvnlQX3GaqK8wbfr6mn9kfQvSRH0OqO+sVF9sBvXNtpht6G9dimPy+pCu5Wl4t4FVszwt6HsN1ucG0gJzi4Xac3hWC/d8T5UZzyIB3gfP0fUiMG4+3wvf5LyTUS6+rXL7bqLvl0zx/boJvq/zZusz4vsLkvZjhyv6BNhXT6TaXzeo/Tg5foHaj5Ph9pzmcdy/tdAzbGIf1Tuk+VPbj23HfBwT9Xejf/L+Doyl9jeN9/cjaR5yjk7f3+bRqfurjk7d3210v7pyEPug9xf78J1kD+vjgf27o+fl2rRGK2yucr25UTrLNDJ9e7dN097iadq7AHB9vOX2Nhvs98m/v2Ga+p3T1D97kvpnj5vXdeP8Hms07nfK+pt3k6y/HaL6W2Em6rQsviiSHva46Jne/D6WH71E27tR1/GD6nezDoNOvhJ0+YJ9X85ifh6cQ3zNrczeAH1El28dQ/ktBxyxsAlDXqzh2C4ThnlJQxxbZ8JAv3dFOPaICctA3wHH5pqwWYCd59gPfiOWCdhljl03YXj34DWOfWzCsnAvmGMtJiwb/aSnGPamCbsLbRaO1Zqw2WhPcGyjCZsDmIdjj5mwn+BYc+xeE3Y3jjXHhn5uxHKQdhz7bxM2F7AGjnWasHsAa+JYqwn7G6QDx46asFykA8f2mrB7kQ4cKzNhP0U6cOxxE3YfYL0cm2/C5qGf4F2Gjf3MiM0HbB7HekzY/XhfAMcumbAHAHNx7IwJWwCYj2PHTdhCpBHH9pmwRUgjjj1twh5EGnHMbcJQx27g2EITlocxvByzmLC/BayNY99uNGL5gHVw7IoJW4x04Ng5E7aEzwO9gDdyzIXnnb/H89DdRR+vS7VtJ4vXo3mdYO5f5xdx0OVQdkvlGigXSOUQlOdL5QiUs6TyaSgL/t9ZfB7KfVL5MpSvS+VrUL4ilQeg/HupbDtV5Tojle1QjkrlQigflcoeKNdL5XIo10rlGihvlcoKlNdJ5QYou6VyE5QLpPJpKM+X+wflLLl/UB76mdQ/KPdJ5V4oX5fK5F3ov1SeB+XfS2UHlM9IZReUo1LZB+WjUrkcyvVSuQbKtVJZgfJWqdwA5XVSOQZlt1Rug3KBVO6A8ny5f1DOkvsH5SHOl3tM+hH6pD72cbsS/j+3VKx9uUO4f8z4GO2gH56aER8nfe3J+N9fTRz/24Dxv+tT9+/W4J2z1L+O+2Rh1KFc10vFvvYo2Ny/JJW9OSRWnAk2JsaNRnkf8Hcb/HbUJ553wjcwD2F75vNq5DcFbpw7lPVL6P1GuN6PbZBoz/0Ztn+uci15Sre9F2HuLu9hjNWMtwbt/D6hS/w9Gwn24jvHeUzXL+E5Wgc8i8+d4s/l8Od28eeoL4PvTUWflG32yfYlVwXK1gt/QOt6oz9gEOhctlrse+F+p3dG35XvQwsUfyntN0XoHsNKrhsVa2VrRP6cCEHdaAXVjZQJxqc1SdsOnmuthcaQ703SyjhOB6TnLdLzJT7d9g/Hu0z2DJ4dG+N9xP+XrRXtq0sc9hwGfti+VvCGjuO3cOyvybplOj///NbE8XN5NO9m2PUX38R7znXAs5inSM4308np0T3DfDOnSd5IG/Em95zPk8qRCOkcbqL5OS0jHUCPyzwHzZse877P63RPeq9HnPeoQdsC998x5xrmpsM7c/g+9XtSHhQ579w5Pp4ZdL9HU2dbkc7sXg60r/W81O1WkZf6tNWcl9qTkpc61zpdnk3MS832jpeRWrU988Ug2kUo54euFzyNso5xA5hv9MwaPc6IxRhG1+p9LqHxD36a825dkJ13KdJEDBZx+3vH2V3EmG/0myN0z8W9RjoPSHAfB+8h/iroGShRuxLoY72P5ZP694uH5uj8djE9iHUvXCtkDmjVD7TqB1rFgZZUtoGe8fM0x2Q4DrSLn/POlCdWBf6/va+Njuq4Enz9WoimWzSCyDbEOH4k4AgHCYGN3UgC9PpDaoGQZH1gYSBS092S2rS65e6WkUCyZOLMyBMHhI1tgQXI+ZjBu94deZdM8MRZy1lnD3OOB2QbYiEQVhJnIoJnD2fH2cgJ1tt766P79ZMaeyazP/bsu+e8rle3blXdunXr3qp6r+vlsLNN+bsFlWLifas5zsRzYNs0+c8E9LdnCvuTv4+9rCTxHF0QvD03Fcf6pYI5ux909DNF3HBmv2l97x2bO/5DlZu8H//XxtIuKa2n3KQoSjswMduFD9NGU6R90UubPxPqo+/X3bHqGQPurXg7cQy9VZxs4ySwyy0bk+V/3MXHdLLstXJvvUm/ndbCZILfFU5jz58ahGXPJb4Tt+xwgNUhzNg/CeB55oVoD4k+bnmg6y57si5y/UBdpOPrwS7UydbPDhS985n2fXU8b/P7XUe3zVwvX7jJz+ucPf10/LzO2dKlzCM3E+dt8/oWbmL7mDf5+9ns/X+n+j2VrxGb8PGflC2o7z1gQ5bY42dC4jkrPQ3Ts72zQ/195gFqP/E8fr4el9me62sOte3cT2znTpE+D+Bn8peJyWcgFIrk3CFyDhfqgIPoP3l+cB1lbjuJ7RubvE3mZY/ReZtAn5f2QPqnRclpdpY2CGnjRer/SNDvJ+B3r8Ge/7Ed7G78/Xywv73CMnK2IcwnNuFZYEPCW+TZkur7PwVC38/ye/rEgsmT6wue6ftVfqHqeXju4v8Bbd43mSX+tDvrkQHw0UrBoOHqJqHhasGP7JyPB58smprX2UrO4nrgmu+OX++XhN/sx2eQWf9rZVeP69pkr2veZJ8rcK2ffCd1dLJ9R6CrHWwH/l9ggDxv2TeJecjaU1PXVlU9WC/W1U9sXLJsiga9trc2JXR5JGPZDfxfTaOhk5zr3Gi4qzPvlaf/YaBeujkwV7i51rjs5nJh2U2Q2+9Abr8DeV0HeZEzd0BO1xuFe0jb0Y/ge5u9g/QZzk81/eZg9Q9D/TKrH200nuODZ/i0FCbOcOPzUDwffjb7iflw7rr+C+XB8TBTBtivrzN7gDKwKanfVxNR/7up/uM3Kbj+8/MUXytS6/8+ov8xAz5zeOtPdAz87Dr+r3sn/g8a9B3ywDx46Sq3gXxDdL1bdXatYNh4FOcB44V8Trh0FS0D35mX1psMT0xJhoLD+E0mG+gtnrX4mTJQYBLGCtx3D4AMBgqy3hvoVvM/T3hiMh/KvsbKLLrxRjevD9cEguqcOkHYdFQy/ORbeEbUdkZv+vor+yv7vncd82RtLuii85JHwZZ327INpZ9Khs++lcNokc+iG4Wdpq8r+7P++NPuPEMX8kv+j6IYn/4G8o7f8Qkqx2Edsoyer/i+o5ufmUjPtJso2JWfOGuR9y1+M2A2feD5sBzUi2VfOC/NPzF9oiim7v+5s/R/F+1//A4J7/93p5dNDWP/b1T3f1f8rMJh4ZffMgp30/M0r3+f8Pbt9ezZuiHxzAm/f5DEm0H+k8mQ0IlMA+iM4S0yP/Q/wM/OvBvq2HV9sdB1Hd/NX0We6XdN8nlg55wDRXOAJovM5xP4s3PwPfSJAlwTcP3HeXWG6YAsAu4G2MOXNybe9cV36dNMqB9LYb207E81Iv4v4+5VBvJu8YnnFIWeoykKE7Y04ZuvGYi9tH1qEhYfbi/4tBO/PWECWhvky6r6Shf4f1vuQ9PdwAPoUl1XmnB2CJaV6+8tneo0CebD5P2PBxPzNh/h/2tkPVJHvtFhJGcrlpF3XLKvZQrXrhdNrewsTPo+R3f8rFBBcJD3+cAfFWUKyvUi96bOifhZ5wl7slVVZ4OqzhpSpwN0Mp88o88U8uN12rB8aQm+DyLzOmOGRJ3tBlqnALQTqvPVUZZZ7H+m/cwfvg1l/N0HRZvudEgbLt//iPfA1ZXkvxVWIb9D6NtdcHpuYXcifwF5/gx9aEt8Z5v+/6kzXu6vyHsyFyDtsftp25rJmZHLri0a2dw1aVx514HY5g78XyrKpHLqlU6v8MNvnBafLBoUjsM8+4edZB6N56uuU3+3GPy2oafoeGHyOzFBhZ7L6l/H53HG7u3r+DtDhutTOG82yNdBr6+DPl8Hfb7+cXy+gvokkW8L0P/KoU71FIx81lPU/uuj3R9r5lc+XM8r6ucXIGNoQ+f0gSL8DsjpuQXEvi2/O7Afx0/W5m92fXTP/v2j5CyAgQL8D8Vd97Ez1kEeEL+WW/pE5xKoN024F3R4/fqssbouys/d12if0zruvbS4SwR9RV1Ng/ruJ/Xlk/omBMOny+8uVdX5SFKdr6xNrhPoZ9b7Xl2XID29mtatTFIdp3p777tTYHMnbCbhd31lnx2QF392oshJZLNkVfu/fEjOtB0hPqU32v7rv+o+ZcBzOzZ34Px/lWq+YhXqXzbBvAFt8hJh82NLyVpk5XrE9RmK7OmQjvhR8g3Dwo6sX9m6TEIAfMKdq+4R6ro/Bh03wv1HBvxv4Z30mfDLT9kyyBn4BwpNcM/3XfJe9tpeY/p378RoJz0bpcfG36mtLZi5T+OGPF33J873XXhfQqfmsPsyVXu47+LnAMCY+hTLygY+sP41qrJ+vjZR1utrE3tkWh1FH8T19N37voDNVuknt9uv56m/f/5Epw/8QPCPCV+LfOL5iOnCV0DepseOTGM/FGYbiM2cLnBO41getJFzQplMsT15qu+J1uYl3pda9Uc864Daha48PuYN1/7ug4lCtCsNoHNoVy7f/9sGPEMG331eZDOBLdgMtsDUgWtFtAect2Hy/4CeAhFsm4GdF/Dz+/j7aE93bxQGVuNZIDCXIedqmgxoO+SnN6aX1JqFuXiuvoznhOC7cO2OpV1nFHo2wUlhGcwx6rrxnfp8tj7ben9ij3InsaHdLyXO8/fYWlZr90X2k/lH7epE+3n/F738lI3rHuA2rWH93PfCANjRf+rGearEzgS5aFPtyZJ3egaJ/n22hu8/UdrTcxu7kf6HtmR9xTx1QP+PjB6fq54Bm9v1YLJ9pN+PQtu2dBXKDuWGfrNBmHf0E9Lvmx/D8nBfIF3Y9HIm+B7TND0jth3ag/+9a/91bzfKsXU6ceZFs6qtpWtmH0trGF74jJyFYYt/nzc3Ibu3p/GdzKL1xK5q7LTzD1A3jJ2nVyfsuZZG+sNsZ0Uk5k8j0dnfT2xbN/N9nSHV+4k/mOX9RDI/zEl+RxHno53sewo2sLVk/buOrn9t5Nxd44a+HtP603Pru+g3y3onbcKTUxfvS5SjKEZyNp4N3/sjNIO2dWsS6fieU0xQug+8q8CcMmF/+PtEr6z+t52PifIZilD5IO7Mod1knYJy+iXIaWFOYi3by9I+W5XA1THcNRUum+EuqnBTBynuLRXuLMP9JxWun+GOqnDNDPdtFc7GcI+pcCaG26XCjX6X4kpVuFMMt06Fa2e4ZSqcm+Hmq3CLGe7TbyRwk89Q3G9UuDMM964K18twP1Xh6hjuFRUum+GeV+GmvkNxT6pwZxmuRYXrZ7jtKlwzw7lUOBvDrVHhTAx3lwo3+lcUN0+FO8Vwv79XJT+G+6UK52a4f1ThFjPc6yrc5NMU90MV7gzDHVbhehmuS4WrY7iACpfNcLUq3FQvxckq3FmGy1Hh+hluyb38/XD8Zm8DjofJGWOJHA5EBxSOnznCSftfi81dSHdDsUxWNnynK+uRhq4LSgaU8Z1rB24I7XiWtUnYcw33RN8Be3cWrrfhGobrDbjQT52GawiuV+HC7zr+AC78lt4AXP1wHYGrD65n4OqFC9/Lx/814ndF8PuauJ5shQvfT26GywcX2tadcNXBVQNXJVz4vVk3XE648LsQhXDhXgSeF4V+fhVc2XAth0uCaylc+J2VLPyuH1wZcJngSkO7DddNsONTcOF7Rzfg+hgucAhb8Hvy+J2IK3Dh8xF8HoT/wcJnL2fhQvs/DNcbcOG5U6fhGoIL/2tzCi6cVw/CNQBXP1z4HlcfXHgmSi9cT8GFdmyyhdoxvj+Ca3Btv+0NR/b4I1GBw+6OmB9jq6Md0dU+/+MBrz+K9zF/y+pQ2OcnPyt8q72tbcFANDYrHaThlbfa6/E2+1cHQj5/+32ro4F9fkEorqjaUlVbXg+hw1VfLJeV2WUHeAYsY3W0uYXzwelqq1317toSV02ZneBXx1paScjoVzdCAyJtodw6AiRdixN4exqjq71NkXBb6+oWf0s40pHb4mln9fG72em8bZGIPxRLlc7JgoGWQKw+EKrnUvwc+raop8mfTO/aVuysryotL6l3yjWyOg6Xq7qGoWfiXRXFark5XfbaEojHIm1+xDOR7CD4XZIr5Nkd9PvMQk5OqK3Fk9Piad1A6l/Rliz/8tqt9eUVTlc1kxMrJ1/yekKhcEzyNntCTX4JigG9iEp7A7HmcBugPcFgINQkReCnHhJikXCH1BiIRGNc3lBjvrQirng5OUwTN2jieRuS48Bq+waMQ/l+Th2P521IjjNqjBMZq+hJXEVP4ip60pkq+ligxQ9Ni/PXFPH7fR2JdH+7xxujtZI4pc3JicZ8gRDKOcxuGb3PDzWoyicCjMdvPf7aVvtg8HlCXr+g7ZcWkHzYKzV6AtC/kq8tEu+GQCgQS9D5HweFbvRJ3ojfEwuEQzxHdrFTIk2XIAGGr2/TyqTyU+TjfKzwJfFTD1IgcaKqlaWVrnqHXCk7Smu2M/pgWyLdvr3GVV2/Va5jca7ypdtKqyuqqFxaI2Evjp9AqDEM8a3+Fvlx4ADVOT9Rr8QVvZi2KhaWWgMhiZgif0RaQTHNHVEJ5QlxsxDnx0zbkU9uoaZGbFJbKBzx+SPxhuKoIXTR3BVtuXzUsDiEvkgHK48WyMdTlau6diuYtIqq0kcqyjfwZG16dY2zoraGCiRBNJNus1xS4nJuyBa+ikT5+PNVCelWMvrH78tdm7sG9Qv0AuJr1+TnPZC/di3nd6unQ1q7Rlqbt/YBxj8MSqisLBBqQ4vY2up94P6gX1jzQO6aXEqXt27NOim7CqTq9sQkmpCzllWYU3GflNMYjIU3eNpAxDmNRO0jARganmDAE0VtpEh/iycUC3hzAqGYP9IajgaINuU0hkH3chojnhZ/TmuYJNIMLZ5Yc44/EglhqTEYfDnBcLg1J9CSHH0cDBMpp7LUIeU8HFyVU7GGhjmeaE4IxiwwTuL2aEfL7nAw4JVI/+4JhfeGhG1gYoCPfImKQbC3BYIxiGGcoQhUVBOkxOnkiLc5XxV3hFtaQfMi+SxeHPQ0RfMT6SUwwNyeaDNPj+utq6qqompXvuQLhlv9fHTlx6vm46ot6q/3xtpnywfNmpGNjqeHS52c/ypXZdl2jkcDX0/TNH7iYWJ0JRBoWwgsdivIDkdNAOw7HzmrJJ+/0dMWjGHXQpcHw00kOc8crxedyJbSsrJqPs7lGocbKqxT63NN1fb6stKtpTWEvzWCiu/KChj/5S5kMI/hAyEvCX1+r8p+kHKryypqqgV1/q3yZmY+WLy0nMfBi1ZUOV1VxDZBvNrl2lJf7arh+UncVR6XG4wwHw+xgXsjgZg/uxGkcM/jnuAqybYy2f6h5c31zpDrimj+CtI92p7i+QKhVmI5if2pJ8bWr6IVos1tMR8obP1eWl88HtHGKYE3GI76E3ouecPggUO+uAsmHgJ6mLeTxMFWerXx+mgrDBl/Ep2X2pZ4PBAFKs9eMsdIwqMHUsXZxCAej+Kkwh+Jx9HIQqYmf3zawMshZryeG+EkelUhcf6CnkCLKk6nEup0vyfU1lq/1wOdGVHXE6+axBvRt+5NxD3ePUl8ERehrjfc2qFOjwaaQp5gIh6M+v17ZrYrUZ8/Bh44oqm/HkdgUr1qJUmqz+9J6pdGbygWVMVbA63J9ImuJfHHqTHUyDfmiUVZ/nByv0dgchCJoc9vZW4/Life91SPot4ItgOIqB60tbRC5mhbS7JeRf0xjqbl7A5HWLnIuno8zJxf1DtqYYzTJqkpKZg3/LlADSuYNlmqcZW5tqIBk7Id7tryLdUr437i36kaoZwY2zYpuxInLSvaVkJbgm2SJ4o6BVa5k0RxcuSPRuPxUikaCwf9LEbuwaVEwi1Si9/M5p1/JjD+asIxsPmOSDgazakOe/f4Y1JNxNPYGPBSRr3NYHmiUvaK3DWNK1b8e8qHFlXtkHHRI9e4abkPg18Bqx7H1JRudcGMSqisKCurd21zlTMLX10pP4wLYYKXq0q43+FxPlGqqZIr68lKlQJbbgmlJeBKwHHURAJNTeApm4Lh3SAIf4s/0uQPeTskprPVflwr+b17yJxGwkHkn0XPpcLmcCSwLxzaKO141AMl+nJzc3cBnROGyGwFaMePtIOsY3ZxPp1+MrVCx0xHXZI9j49DqRC9+UapMOBrh1+wE/C7JxAMRjcyOXWEvBId2FK4sRE4nmV8S4WNPkZfRUyB1OqJxAIgj7hJmGknaKZKMCVSsTPZrqF9kQqJK6kHIrgF217viUTgFm04uaX0ZbAegqmHx4c+J8rtKyJ3bJOrdgmVEZQaGa0xfxC6J0Yn6NXN4b3Sbpjk+WBIxCB7zDPD/kk7cmKdOeHOnJbOnKbOnMbOHE9cvtXUviTnY0ansLQcGAWtw9/iYvgtcwFmB/HFrAQH9exxSxy3y1KhXFXVWeUE+oeB/2KwX+C0Q+Avg8n2XCosdmKXtRDRV4PJl/iiRe0HCFm8vjjFDP8hFYK8oD/4LI/5PCK54oQ/IvHShL+qBk8mQZEJv8b4Ig3f8bDbVe5w7WKdgfTEFfLVZJJ/ZJxSeMQfCeegH5VmmQcQPBMwyJrqHXHCcYVL+GXGT2VxXSdpL3AVX9TtEmTvHmm3B5onJOs1y4XTRKgG9IzNbvlUQOWXoWzwP0hcWgbBDlgC7uLtjDPvoFMNiU812AQ73rOq+Ym0Aya5nTDB3UXywRRGxWFiXpOQKWl/G07VA40B8AGkj5KnQzPnSVIhkwaxAPUBMswSI47sSmyk5ZLyiCGX4jOVGfOxmeXF+aKjLwyjmglRO79SzffAEoVIKdCRKkakHfEem9neoL/JAxY3qcXqeSWxNNIO3rpd1D7SvSmkI/YczBgYrMA+P0GRDS3sncZAU/I8VtpRXCaXVHM+HGiapUCj1IgDNRCVdgdCnkiHFI5IzZ6oFG327/ZgDTPmx8AU5EjW9xpPu+SQKoNtTYGQ5IJJd1uMTcMS823amEJw6PBL9pKw48Lw0xjaiHYJyudMwERfYjYJ/EAgBvzwnSjtvD6pWLQp0g5PpCnKvJAg1AZjEU9Oowd6yM8ZA4cAEVBn1HRSZcAf1a4bZuV3ZgXFWDIsbiM5ICFgB5YkKJ/4+iSpGDD/ng4caVjcLtW8OhA3FIuXfPnOpXd95e7MhYu+lHXb7XdQ7PYiw53GArdIHxyeypxWGuC+d+m0cgTCxXdNK29AmH33tGIyCoJtOaRDOJk9rZyCsDdnWvkIwv7V08r9aYJwNm9aaYdw8TqgnwN427SSB+GpwmllAELbpmnlBoTN8rRSmQ7lOqaVZyCsc00rpyE85Z5WbmK4ZVpZNVcQTK3TSrYJ0v9yWhmdB/TfnVaKYJrT+wbUlyEIU1PTSud8KG+eopy1CkL7QkUpWwD5ShXlGXwYCuEghKOVimJbCGGNohyB0B0E+i8Bn22K4syCfB2KMgDhFITDGN+nKB9hHELTbRDfryirIJyCsBLC0R5F+RjCU99SlPtvB76eUpQ6CJv/QlFehdDUqyifQNgL4WKQtOlpRSmEsP2QorwB4RSEExjvU5S0xRCHMBvC9sPAP8YhbMX4s8AvxiE8A+HZQUXpWQLl/Q2UA6HtFPCJ8dcUpf/LIKcfKcoVDP9eUdrvBH5+oiinIJyE8B0I3T8FvhD/3xRFwoOn3oT6IMz+OdQH4dl3gH8I288DX3cJwpkLUA6GHyjKJIaXFKXmK8DPr6AcCBd/pChZdwtCw28VpRP0JJM/ANtXJaS1y4Y7MwzCYtQ9uIqs0wp5h9W4VFwodzvTZUEAEQv3w3UFyiHPn+3zZMGeLi/HeQxcHy+ZVp4ik0zAnxBPGpzWvIXyE5VWAbJ/eJXoLOp3zZenlUw8m3q7tRLSTxocA2nycaPjhFh5RR6Xr5ZaBQdksFsrB9KOG7EgoKq5Mn71ITNNcVoEnAYPI6+g+2n4TexiqPOkodhaBLRi7Qmx7KqdUdstiXzBE6L7qu+EKF+VKcphLSLFN5wQvearLgtumCyGto1IMGbScMOLlHtCLCa8ig8fNz4y7jCzJjksFXDrwlunRYwdN7rGtxw3yuPQ1/hMEcqxrYCxhOWIPsLaNkIeIvclViFdpmgX3m4nt1SWA5B3YOW0koFychJ5lvabjs49lv7SHJQKYdphnehJqwUOKpCD8SuXxy6NOi0dgChLIGQLvsz3MZS38xswPg2sf7AgB5bkRAG7rA1QXjnkLOU5nZaHVLFncA8L7c4qsAXYHsdJg/1Yut3aY0DJywNp9hfn2ftNMpQKEjghOqG8sqNzfR/Io/Il+2WZ9KycLsvYFx+OyRZosh1CKODFef0m3i7W25uPzu0wz8hqEXdfkgEL1aPODQM/JrRh+J/CEusNE3bQj0m/shiMHfxfCtA13Ac6h3yXA7coRqzMQZs+mAakdS/NEXdctsebPHbJCQkJgTPGAubLDkvDZfdLc0rMl+0Wmf3IluLLQiXqNvCS9iCMA+y3UmtfBjYGRAUCOW6sHkgTH6at+ZDqnx0o1M1miXaOE3ainTfiWz/QdyKTu3UiDYcejBko146trjZTETksJUxWVgHrmEiUXUJIrDhgP5QtbkpG9NQEcsksAJuOulFsHUJql5lQOiylJw2PflhCB5DD4gZ5mT8ssbg+ZH3ghLxHChlvdAw6rcNkRLFBYidjKgh0AxtBd4xM/44bB9I2W3tEwp27GxvxLcjhBtbT3dgBssUP8ZJ43GHBl9hPQzk/AH/0CR8X2IE4bGqJ1omNV+XxVjq0hSkg+QjoY85ppWY5qxd7dOvzlhfMqHXYtZAXxq21bwXhpLh7YUk38CPPCWYZ80TgoBzanV4sp5cwPnBMffCLi+lB2bLr8AL5WavjSIbxE8PBRfKhhXJfpvzcfPHFc+dH3n/o3fcu7D684FnrkYzGg4sOLezLfG5+rfmcfF4esb/vsLSTO/l943bDu/J78gU7JS3jpGITFlJsJomg+bVQXBmlETdTrN2yh9+Ij/J8xZhNEF6FvpwAuzjaNK2U4eyhAtrOtcplvTH/4CJoOG2reIZwbietAf7lIxny8xb5BbP84jwZhvTRufKxdOdLc4wdBjPyDHXa3wemLsq/kMkYlcfkyzLrOy6mcw5L2/mRd997/8LFX3wwemnssgv5wwY8N/9IBu8AOr6crFR5tlJLk0qVCeupi1INJtq4PUlMlKfOuTmJ8JHUhOK/JFFW3ILyWBKlIzWlgIvaPphDteNXK+ew/jo696QBG+vm2aA9R9CilFkHD6TxEhLNFoepvrrS3U6Vql54/713R86fky1QLL7mMgX1TByYVupWM/+GeUvB2p00HFqIguODQNwOOgBGHmw6qDfotkZD4uoxkGZcbTinbuuVkoOLUveR8YB4LqUiXZHZsE8MuvMycPdFuz3O/c+twrmkDoApxIfpUG56Sbrb/m8p8Z3kNpbdqo0VybSuW8rjhOFfQ32bmEztuBU1mEno849hPl42NK34CpkPfHFeopUua0+6pqWPxe0Z6XO72iqQPhffjst29FLpTEkiA8blooqoJAXRXxioKXzXnjAAqAtWYXOyFoA+fwDzhfR/dbcVq7gom52LfZ/PqOAGOd4Pgyh2fVoJ4uTZTeZRAzBu3Og1iRcrBQEdnUvnQKVkPiQ2EuEF3r8wenn/L6Bh1A8zT3dlzAl5aQ3aBri7d4LQn5u/5XnLNiIZu3kUBojlUTOV0GU7Lao4XpRFPExZfnHeN5NH1mVttfZbVOscvVyD3tE/etlF2uDHih2WLVh4BRn54o9o+R/U8Qo9Fz/Y8v6FRoySUY2s8jQszG5mOdAQ4Tt3PbAm7P8jzN/xXd9KkCUyw1mx40Ri0Aj87DyWLv4tsIvqQLTg0qgDUmbhXHSZx2Q1ndMSMI85LDvHSo6lt5lx0mkeQ685RmxhIfRnGqxHl4uwHnoQEJuBhyPzB+Y4Txifz3AfNR2b+1L6cZwgnBQd1pGvU21yzAneLp58doF88EvyIbCKC+2Hwelb5RdAKjA25slvGsRPqTbB8FSeOPilQ4v6Fh7OfHbBc9YXLC+a++e9aTDeY1RkOhWgbo/0kp0Y76SZxsULMM+AqtWFHJn/fAYtiHI4MOd42gnjSfFNA3AW93vGH89JMOGajQlx++cQhBLpntnScQg4YR0fs8G6mq0lj8BVZ8W3nmFNj/+Bc1lHlsEKD6eTMO2UcdoKGgVOBRZhs845oAXoWMCrvDRHJgtD8Tlzkq+wc18BwuKrA5zugvb/7OAi96GFtedLz8k4iCvPV5ip38O36W4AX/2bFOUmzkGrgBM6xqklPGl4br4TlRXHsHXkQBodG8yxvskcq9arkrJxXYT7GIUORfHdwfUo4wUzqmWJdXA+VVMoeN9x445x93FjZNwLDX9uvgPa3m+yQ1sPLXRCo2FJ8rxFLDnPJkMX2dgd38KUGur+xQVYsMzH0mmpTPUbDi2k9oqOtqNzjxtj56HzLoKHGHfPTGyPJ9bNTHRoGCiFpYOaA7ulzjzutDj6TVtHndrsWw8uquvLFP1UeS5+cAmMFtCSLt1G13ROSxltmDavWG7WVO0Yly0R8EXntkCZj7MiRy/VUvodakv9vMV5Lk5QQgmqEjU4Dy5qO0davYcuLLWV29GLwqgcsROqzeqSAXlwkZNmLz+8YAfxiNhXZJ64l1ZLOQaVpuWBQ+PZXaxNgIi+C9zJ4/iOEp693F6nKO+YmE/GuRyqm/Ok4fCCrdbhZeo5H/Vz1ECKr9FFP0z0ZI1KOiziJ4cWlpD5WhU0pvS8TIVUeW6kAqQLCot7Jzeh7ncaFKUG18QPWQefREs7w6SC7/xbupugWvzIYFStwlYNDorB95FqFgnCBZ+i9Ajx9ZmDrM8eoqtBpGkHmjw/2Fw1TWVipwhpBoDmmc+hGQaayc+h+QhonI2pafpx/fslsFdAM5HG1ojo0cFuMY8OBj+jBJaI4JNeMOMoPZbugN7tN8GSSNymnrnC2tOV8LDEchtmm5xAgdTPgsNKzm8RK+mc7iqyC9cPgLePHlWUt0XVvprD2oNjXrX3BJZDJvs5Im5GgEl0siSHhfbLx1BOsCW1HHDvIjNLEM4CTZGokoOD7AztOpYe39mpHqOTia20iit2a4PGD9eMXR6/Svn3QZmnw4qC+1lCibWV7PedEOOsg0sgZh6Kfoxy7mIpdgs17pT/V6GcjMc0elWZrFcjQNN8Cxps+ydA8zbQ+NIJP2SnAhmqVMmSMyR+m8nSwoQKzB5Lbx0rY4xaKmFm4sbJRC1dt4w7uCDKzAwjW7aNqdsRuw3ksffW7egHmsz2W9O8ATRBoIlpacoTNBNAc/Zzykm7HeY/HbemyQaans+hKQOaK7egeRvffQEa2z5FOTs/SZeHRdz5AtUtJkoGqlxHNGz7Fa4KMtDEPZ2dLD/snFacTKwbxx28E9UZdvLhd9xoXGrAwTWOnesclxMJ5aOXKscu4xYZ9DV22rgzkegkeSrIxi7ul9nAxxf9JYwTqkNDXIfEh8zxUecyx9W4Af29+PZxI25BxSCv87tKYh+WygAtZAfLIQyh/QO6soMw7k0zZQUTCCdZdDvIFg3ddRVBNb1mWAG4ktbS9nG1ELkxShqtUZhJlFpghrxtbM+x9NBYMbdJ9iSZyhb3sfTKMRF+G8ZazIl1xRU72BjcY65cDOPvBYXuD5eg/Zw5tkDwMHdwWLaZ4yZKtoTM41gG2mJ8fhI7BnM0bouftZL9KmaL3bBYhd7lK573ZEh51ppYuOCa9QWzg2xMoIpAn9ElbHyGyeeVIAu66/S+feYGBFg3h6oS4A33HvOWCMLoCUXJoPuk9NlFXXyb08XuHNwXNgD9mZOpxwTqw1NAkzWoKDsNKpo+orasONmSjfYP6MpeVhRJtUd70uCP0zAzLiDtKNAWfU9RLpAHk7S0k4adrBfIzjuhJeP/y2ATkZY8Q7EOUtqKeFNQ37OBZugU2PC5pF+xBSjxLTCebjOMuxJKLw4cN5bGFY7MM3yQN2tIUYbE5LFSfdwYjmsALkVZH1bER/CQIa6hroE0r/mK01JBzKiAL3u+AeUG/4ui2OYkjY8JrV8ke5cO6PH4biZdUjTFlVxjOqAVZWatNlgEfHkl704Y+z9W6N4z8x24cAA3AKXuJDU4iHWijlKMD0XQp4fG5Cusjsswjg2YkT74ISg7oKjzIGjy3GIQ6jv7OtSX8J3H0k8acAwMpLlemlMOjQMxQvFkpF5l4hxzWFtxV4IJD1NYLWNOa+uMRTPYGig+Y6kg7PwJrOPm0X4SybY41QTMSn0fnWNA0x7pN5XAdP2gOSElsHTi91jUfoUMIJIRelLUVFlG1gmjlx4hc/6u0XgRMt/NhDnwKEcKS1H/4efmf1eULPXY20u1FNPfwfS3wSbj2s5tlXA34C3yHEDQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHXTQQQcddNBBBx100EEHHf4/AwNcCgOMDzopPo+FEzeNcTqEJXOFpPjXWDxTU24GCwdtNJzP4osXirQcFh9h5d/J4iYWfpmFoyx9qSb999NKGMNsWpwwh+F7GCPpLG5Lo6GZxfsZvxbODwuNcc5pBlascJbRZ7E4iwp3sPBMXjxjK/68ukDk5bWq5cTzDS9JbsfU7TScp+HnKyzkfEwrtL0Sy6+wOE+/weKLWQGfsvg//99WoO40fRDpoMP/I6CoAOO9ErUgk3eJs9KfYunD0uzpkxy/bPZ0ieFtKdKbGb4nRXo/ww+lSD/L8KMp0k1fpfjFX509PZvhm1O0v4il16XI38PwfSnShxl+JEX6JMNPpUjP/BrFS1+bPT2P4YtSpNcx/OTSFPJn6aMp0ttZ+tkU6b0svS9F/Wd4/hTpEww/lSI9czlr//LZ090MX5civZXhe1KkD/L8Kdo3xNKLUqQPs/SRFOVPMvxUivTMFRSftyJF/zB8T4r0Uwx/NkW6cA+T3z0p9Jvhz9w5e3olS29Nkb+X4YdSpI8w/I0U6Yu/zuT79RT9x/CDKdJHGH5Sk87tWcOrhqT56rCYNqu9G2XxG0oy/QSj19q/YUY/8R+T6QVj2qz2cIjRZ76STC8xeq19HGT0fb9Kpi9i9Fp72cvo8yxiEn0Do9faz3beXkMyfQ+j19rTTDbRbvjnZH4GGb3WvnJ7euOmRv6MXmtv6zj/P9DIn9Fr7a+b0Q/9QSP/tLRZ7bGN1/d7jfwZvdY+ZzP6nt9q5M/otfZ6MaMf/Kdk+gZGP8N+8/J/k0zfw+i19pzb76Hva+TP6LX2ndvzvnGN/Bm91t5z+56nKX+C0Wvt/xkWL7qkkf+ctFn9wSlGL32kkT+j1/qHft7e72nkz+i1/qKX0Q/+WiN/Rq/1H+2MvnVEI39Gr/UnzVw+Gn4GGb3Wv3B/MvSyRv68fI08uX8pOq+RP6PX+p88Hv8HjfzT02b1RxLn/yca+TN6rX8ycf7/XiN/Rq/1VzeY/8jT0Dcweq3/GmX0Q69r5M/otf7sLC9fQz/I6LX+jfuzoTMa+TN6rb87xcvX0E8weq3/6+Pl/1gj/7lps/rDHkZf9JpG/oxe6x+bGf3wkEb+jF7rL+t4+Rr6Bkav9Z9uRj/4nzXyZ/Raf1ricORL2SXltSulNQ/krsldI63NW/tA3ro166TsKr9PcntiLCFn7Uq2v5HJCi6Rlxvu86yJ7wUVsj0geQH8NIXaBAPujqQZhNxoczQWiXl2C7mhcMyfC2m5u9sCQV9OwCeQWLMn2izk+jpC0Y4WGsYiNOVxfyQaCIeSIvWQFvEHPUjI7lqDMSE3EArAb8zfDr+NEIG0sM8T8wi5/ub6xoinxV/f7IskYkBLk2O7o1Gavd4TiXg6aHZ+jzRYC5RGePO0BLzATzhGk4Rcktsbbmnxh2JConW5nlgsEtjdFvNHKVYV/3PBwvae4r0pJofLNfTa3Rzch/rfihLm2fh+Gw8zxOT9M5N2fcV4EDX7cTx0ZyTqNary832wPIYXNft7POT7eer9zCS/z/bKeH6+P8bDdEMy/xrxCC6298bjfP+Nh4MquYmztL9Glabe/+Mh3//Tyo+3/5ssv12z38hDvj+J+W+fJX8zkwnfD+2xJYc7tet1TTykyT9hSw5to4Zb5o9p8vP9Xx5+nv7tY/m5/IpYPh5y+cXnqZr8BzT5bUxxeVgm3rr+Pk3+p+4Vk8KPl946/zGWny8Lhtl+9vBNMWmfPBX/L7M+5fn5fvkIy59puHX+v4HLqtIvbX6tvpo04X+Fa4EqP9+PH/2C+d/k7ReSnydMfE5+Du8w3eH5J1n+Sd5+MVnuJo0cLmrqFxR2p9CMlbM9EFGV4+Xy1/RwJct/Srx1+8c09Q+x9eSQSDG2jFv334Sm/htW5p+tFDP0OfrzG1Z/nnZfguXPnb358fB/qp5dEHu3gK33Fhi/0PgFry78nj2LUEMhy58p3Np+J/WdCspY/izDrfP/H76m3N+gFwMA' [riscv64]=$'0 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' 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' 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' 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' [s390x]=$'0 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0251bdfe91834ae57de7e959c1d799635ff87875..f801262d625aab384c079bef3aaa231bb7b14964 100644 GIT binary patch delta 359 zcmX>xjq}7b&J8=5M3!kj{lIoC=44i4;IwGX!)@M2KR#?e!?gVj6JrAlBja>mc1CM^ zpWYM|1CQe_Dh>=l@L%BQ&wLh%qd)6iR198=@XIs2*!=t7|7Hu8(j1R&(dAx@3{KrP zT0Wi6c1Zx0zfhZgo}E$3g29b+709pfD1 z5A(~n0L2*?rWbH97BCh~f5^cYBP06%|9}2%M_=-SX!!<^d~X0_!!JhuzOU0GIT`&K zr%hkU$tca(H~lClqXlEY^naX;(M&)8PLJkdJjSRqU5T5~gz@|IaBfCN#;x0DaxZ8j|6r@D+41dWAp8qzZjRxGGxjq}7b&J8=5L;_D)thu;9_7P{N*tv{J3=4Ah-P+N7hH3j5CdLL9M$YNJ?2Oj+ z$6Zuh7=Xa1H$}zZzkmnhjiW#F8M++=j{dB7Q8DOrQE_-J!Y|M8V)gHT|C=pXN^?BA zMdy1lGB|bHX!&$L+a&?i{6g-}zyBVs2P$rQH2;t&_4ELms=)}9@aSee4OHvat)lUo zpI;tm(~D%NIpVuGfC|JsdP`I^Tsoh>xC0ai8FAmEm$hQLC7F=7;so2N@fF zGV=GQPxs?sl$u_^!C1gpHT@w6V~mXK|NsB_w;g>c3Zms3fa)1~0~i~AG4l8QogT@_ z=+8KB`bthlX~t>Ok8(0vFh)%O$H^GY#Q1M|G#BGBMw97E+>9oS|EGs@GdeQv-9D3> u@q90npxE}TnT$UY*bS_VjIB(}wrBogTrSI4G+j`FNsQ5PyM_dlf-wNURD|sS From f135cd000654849bc541f435f1c278c74e8b25d5 Mon Sep 17 00:00:00 2001 From: jkool702 Date: Thu, 21 May 2026 17:11:00 -0400 Subject: [PATCH 06/10] initial test - superscalar prefetch engine --- forkrun_ring.c | 1 - 1 file changed, 1 deletion(-) diff --git a/forkrun_ring.c b/forkrun_ring.c index 2b3d0c84..ecdb4551 100644 --- a/forkrun_ring.c +++ b/forkrun_ring.c @@ -1013,7 +1013,6 @@ struct WorkerBatchState { static __thread struct WorkerBatchState prefetched_batch; static __thread bool have_prefetch = false; static __thread bool prefetch_tokens_ready = false; -static __thread size_t prefetch_batch_argc = 0; static __thread bool tl_drain_escrow = true; static __thread int my_numa_node = -1; From 88e7e174d784490aff4e438aa0d29a71752840ed Mon Sep 17 00:00:00 2001 From: jkool702 <107448833+jkool702@users.noreply.github.com> Date: Thu, 21 May 2026 21:17:42 +0000 Subject: [PATCH 07/10] build: update embedded ring loadables --- frun.bash | 2 +- .../forkrun-libs/forkrun_ring.aarch64.so | Bin 137416 -> 137416 bytes .../forkrun-libs/forkrun_ring.ppc64le.so | Bin 202656 -> 202656 bytes .../forkrun-libs/forkrun_ring.riscv64.so | Bin 104032 -> 104032 bytes .../forkrun-libs/forkrun_ring.s390x.so | Bin 140840 -> 140840 bytes .../forkrun-libs/forkrun_ring.x86-64-v2.so | Bin 142152 -> 142152 bytes .../forkrun-libs/forkrun_ring.x86-64-v3.so | Bin 150344 -> 150344 bytes .../forkrun-libs/forkrun_ring.x86-64-v4.so | Bin 150344 -> 150344 bytes 8 files changed, 1 insertion(+), 1 deletion(-) diff --git a/frun.bash b/frun.bash index 3626bca0..543fd1b9 100644 --- a/frun.bash +++ b/frun.bash @@ -1739,6 +1739,6 @@ unset "b64" # <@@@@@< _BASE64_START_ >@@@@@> # -declare -A b64=([aarch64]=$'0 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' 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' [riscv64]=$'0 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' 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' 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' 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' [s390x]=$'0 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' ) +declare -A b64=([aarch64]=$'0 137416\nmd5sum:35a780a180a5931ab79e8256baedbbe7\nsha256sum:f0b70453287b932c7455e1db9b8508244c30bc55cffa5ea9410dc03133572fd5\034\035\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' 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' [riscv64]=$'0 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' 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' 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' [s390x]=$'0 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' ) _forkrun_bootstrap_setup --force diff --git a/ring_loadables/forkrun-libs/forkrun_ring.aarch64.so b/ring_loadables/forkrun-libs/forkrun_ring.aarch64.so index 2e6d1889ab3483226562c0bd670c182c80b19394..fe5e7c9645fb5a35e9d2e6974100e5ba822b8876 100644 GIT binary patch delta 59 zcmV-B0L1^uu?Wbq2(S1Haasmhd37kmpBQAr!2kdN delta 62 zcmV-E0KxyDuMD8C46qOa6v`E{jUVKlfqVvl;SUAL4am0Haapghd37kmpB෪_CIA2c diff --git a/ring_loadables/forkrun-libs/forkrun_ring.riscv64.so b/ring_loadables/forkrun-libs/forkrun_ring.riscv64.so index 6d5dfd41a3333fc56ae47bd0aec18815ed577770..63f3a9cfbcbf0d0bc8841029ba79304115afeda8 100644 GIT binary patch delta 59 zcmV-B0L1^`tOnq$2Czs16jGC%@7z!kUEZA$_&(iA#b`%7w1Zp%w_E}N1RVj^w_zUv RG9?8uH##shx0pl$$Wi<17Qg@i delta 59 zcmV-B0L1^`tOnq$2Czs16r^fWaa-=QJZ$1LLc!Ot<|;hinuA;dw_E}N1RVk9w_zUv RG9?8tHaajhx0pl$$WaNP7f}EJ diff --git a/ring_loadables/forkrun-libs/forkrun_ring.s390x.so b/ring_loadables/forkrun-libs/forkrun_ring.s390x.so index 9c84a135cdb270d9f92c872163a69abb9ae9daf1..be187c47393993c70400909672b4655835c28cdc 100644 GIT binary patch delta 58 zcmV-A0LA~P%m}E=2(S3BNM-w|3K0pi+1ac!EB+&uY)84wjP7P6JcG;vx6A?o9DM=)x9NWY RTUrG$GCDIcw@KOo|4?6G8uI`E diff --git a/ring_loadables/forkrun-libs/forkrun_ring.x86-64-v3.so b/ring_loadables/forkrun-libs/forkrun_ring.x86-64-v3.so index d75b1831fe93c052d712836befcf2ff4e1c7e697..028e8065f1157bb180722cb4db395526b10bcf65 100644 GIT binary patch delta 59 zcmV-B0L1^umI=s~39z^V6seVAgOVkodM^?W9hXfZvvw}p@q^3)x6A?oOp*cpw;7cI RD`f>SF*-Fkw@LZ||4`!U7uEm( delta 59 zcmV-B0L1^umI=s~39z^V6b|MQJRQB{CDANGctvO`jmBXWZiCDMx6A?oOp*cqw;7cI RD`f>RGCDIfw@LZ||4_`P7cu|< diff --git a/ring_loadables/forkrun-libs/forkrun_ring.x86-64-v4.so b/ring_loadables/forkrun-libs/forkrun_ring.x86-64-v4.so index f801262d625aab384c079bef3aaa231bb7b14964..0f02872ab5f8b9f3e0bc95c94db55f71f7abd44d 100644 GIT binary patch delta 59 zcmV-B0L1^umI=s~39z^V6g0v+%WaAK?^4kzPmZ_v1$riZWP{8Cx6A?ooR$Iow`rLH R`(OnzGCD9Zw`uwT-%v(j8t?!B delta 59 zcmV-B0L1^umI=s~39z^V6s9TV@CL?Q$!cLymRl*qhD*iq;e*Tqx6A?ooR$Ipw`rLH R`(OnyGCDIiw`uwT-%wd18?^uc From 6f3149d5f733d745f7b7e68bbef49288d66d1337 Mon Sep 17 00:00:00 2001 From: jkool702 Date: Thu, 21 May 2026 21:49:16 -0400 Subject: [PATCH 08/10] new NUMA benchmark (prefetch) --- BENCHMARKS/benchmark.NUMA.out.txt | 5832 ++++++++++---------- BENCHMARKS/benchmark.out | 8544 ----------------------------- 2 files changed, 2916 insertions(+), 11460 deletions(-) delete mode 100644 BENCHMARKS/benchmark.out diff --git a/BENCHMARKS/benchmark.NUMA.out.txt b/BENCHMARKS/benchmark.NUMA.out.txt index 0a7b53db..ed18b966 100644 --- a/BENCHMARKS/benchmark.NUMA.out.txt +++ b/BENCHMARKS/benchmark.NUMA.out.txt @@ -12,11 +12,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.142s -user 0m6.360s -sys 0m20.424s +real 0m1.143s +user 0m6.433s +sys 0m20.603s -CPU UTILIZATION: 23.453 / 28 +CPU UTILIZATION: 23.653 / 28 ----------------------------------------- @@ -34,11 +34,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.126s -user 0m6.276s -sys 0m20.502s +real 0m1.130s +user 0m6.330s +sys 0m20.625s -CPU UTILIZATION: 23.781 / 28 +CPU UTILIZATION: 23.853 / 28 ----------------------------------------- @@ -47,19 +47,19 @@ CPU UTILIZATION: 23.781 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 1 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.135s -user 0m6.427s -sys 0m20.542s +real 0m1.131s +user 0m6.533s +sys 0m20.627s -CPU UTILIZATION: 23.761 / 28 +CPU UTILIZATION: 24.014 / 28 ----------------------------------------- @@ -68,20 +68,20 @@ CPU UTILIZATION: 23.761 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 0 -real 0m1.132s -user 0m6.399s -sys 0m20.605s +real 0m1.134s +user 0m6.413s +sys 0m20.787s -CPU UTILIZATION: 23.855 / 28 +CPU UTILIZATION: 23.985 / 28 ----------------------------------------- @@ -90,19 +90,19 @@ CPU UTILIZATION: 23.855 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.199s -user 0m6.495s -sys 0m22.111s +real 0m1.230s +user 0m6.539s +sys 0m22.112s -CPU UTILIZATION: 23.858 / 28 +CPU UTILIZATION: 23.293 / 28 ----------------------------------------- @@ -120,11 +120,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.200s -user 0m6.423s -sys 0m22.259s +real 0m1.212s +user 0m6.568s +sys 0m22.319s -CPU UTILIZATION: 23.901 / 28 +CPU UTILIZATION: 23.834 / 28 ----------------------------------------- @@ -133,19 +133,19 @@ CPU UTILIZATION: 23.901 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 379 assigned | 381 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 382 assigned | 381 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.198s -user 0m6.452s -sys 0m22.377s +real 0m1.205s +user 0m6.697s +sys 0m22.326s -CPU UTILIZATION: 24.064 / 28 +CPU UTILIZATION: 24.085 / 28 ----------------------------------------- @@ -154,20 +154,20 @@ CPU UTILIZATION: 24.064 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.204s -user 0m6.531s -sys 0m22.457s +real 0m1.206s +user 0m6.775s +sys 0m22.384s -CPU UTILIZATION: 24.076 / 28 +CPU UTILIZATION: 24.178 / 28 ----------------------------------------- @@ -176,19 +176,19 @@ CPU UTILIZATION: 24.076 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.888s -user 0m25.089s -sys 0m22.012s +real 0m1.890s +user 0m25.372s +sys 0m21.945s -CPU UTILIZATION: 24.947 / 28 +CPU UTILIZATION: 25.035 / 28 ----------------------------------------- @@ -206,11 +206,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.896s -user 0m25.353s -sys 0m21.954s +real 0m1.903s +user 0m25.445s +sys 0m22.012s -CPU UTILIZATION: 24.950 / 28 +CPU UTILIZATION: 24.937 / 28 ----------------------------------------- @@ -219,19 +219,19 @@ CPU UTILIZATION: 24.950 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.892s -user 0m25.441s -sys 0m21.950s +real 0m1.891s +user 0m25.372s +sys 0m22.077s -CPU UTILIZATION: 25.048 / 28 +CPU UTILIZATION: 25.092 / 28 ----------------------------------------- @@ -240,20 +240,20 @@ CPU UTILIZATION: 25.048 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m1.897s -user 0m25.393s -sys 0m22.204s +real 0m1.900s +user 0m25.663s +sys 0m22.140s -CPU UTILIZATION: 25.090 / 28 +CPU UTILIZATION: 25.159 / 28 ----------------------------------------- @@ -270,11 +270,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.665s -user 0m1.582s -sys 0m13.773s +real 0m0.661s +user 0m1.596s +sys 0m13.863s -CPU UTILIZATION: 23.090 / 28 +CPU UTILIZATION: 23.387 / 28 ----------------------------------------- @@ -292,11 +292,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.679s -user 0m1.573s -sys 0m13.743s +real 0m0.661s +user 0m1.580s +sys 0m13.867s -CPU UTILIZATION: 22.556 / 28 +CPU UTILIZATION: 23.369 / 28 ----------------------------------------- @@ -305,19 +305,19 @@ CPU UTILIZATION: 22.556 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 381 processed | 1 I stole | 2 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 3 I stole | 3 stolen from me +Node 1 (Phys 1): 385 assigned | 386 processed | 4 I stole | 3 stolen from me +Node 2 (Phys 2): 383 assigned | 381 processed | 1 I stole | 3 stolen from me +Node 3 (Phys 3): 377 assigned | 378 processed | 2 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.2%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= -real 0m0.708s -user 0m2.466s -sys 0m14.171s +real 0m0.707s +user 0m2.479s +sys 0m14.223s -CPU UTILIZATION: 23.498 / 28 +CPU UTILIZATION: 23.623 / 28 ----------------------------------------- @@ -326,20 +326,20 @@ CPU UTILIZATION: 23.498 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 2 I stole | 3 stolen from me -Node 1 (Phys 1): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 378 processed | 1 I stole | 2 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 2 I stole | 1 stolen from me +Node 0 (Phys 0): 383 assigned | 388 processed | 8 I stole | 3 stolen from me +Node 1 (Phys 1): 382 assigned | 380 processed | 2 I stole | 4 stolen from me +Node 2 (Phys 2): 383 assigned | 381 processed | 2 I stole | 4 stolen from me +Node 3 (Phys 3): 379 assigned | 378 processed | 3 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 6 chunks (0.4%) +Total Cross-Socket Traffic: 15 chunks (1.0%) ================================================================= 0 -real 0m0.704s -user 0m2.444s -sys 0m14.150s +real 0m0.711s +user 0m2.495s +sys 0m14.248s -CPU UTILIZATION: 23.571 / 28 +CPU UTILIZATION: 23.548 / 28 ----------------------------------------- @@ -348,19 +348,19 @@ CPU UTILIZATION: 23.571 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.703s -user 0m2.401s -sys 0m14.072s +user 0m2.400s +sys 0m14.155s -CPU UTILIZATION: 23.432 / 28 +CPU UTILIZATION: 23.549 / 28 ----------------------------------------- @@ -378,11 +378,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m0.704s -user 0m2.414s -sys 0m14.105s +real 0m0.703s +user 0m2.365s +sys 0m14.214s -CPU UTILIZATION: 23.464 / 28 +CPU UTILIZATION: 23.583 / 28 ----------------------------------------- @@ -391,19 +391,19 @@ CPU UTILIZATION: 23.464 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 382 processed | 3 I stole | 2 stolen from me -Node 1 (Phys 1): 381 assigned | 383 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 384 assigned | 381 processed | 0 I stole | 3 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 385 assigned | 384 processed | 2 I stole | 3 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 4 I stole | 4 stolen from me +Node 2 (Phys 2): 380 assigned | 380 processed | 3 I stole | 3 stolen from me +Node 3 (Phys 3): 378 assigned | 379 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 7 chunks (0.5%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= -real 0m0.751s -user 0m3.192s -sys 0m14.573s +real 0m0.750s +user 0m3.205s +sys 0m14.676s -CPU UTILIZATION: 23.655 / 28 +CPU UTILIZATION: 23.841 / 28 ----------------------------------------- @@ -412,20 +412,20 @@ CPU UTILIZATION: 23.655 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 385 processed | 3 I stole | 2 stolen from me -Node 1 (Phys 1): 383 assigned | 381 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 378 assigned | 378 processed | 3 I stole | 3 stolen from me -Node 3 (Phys 3): 382 assigned | 383 processed | 2 I stole | 1 stolen from me +Node 0 (Phys 0): 381 assigned | 380 processed | 2 I stole | 3 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 382 assigned | 384 processed | 5 I stole | 3 stolen from me +Node 3 (Phys 3): 380 assigned | 379 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 8 chunks (0.5%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= 5965 -real 0m0.753s -user 0m3.278s -sys 0m14.570s +real 0m0.750s +user 0m3.281s +sys 0m14.628s -CPU UTILIZATION: 23.702 / 28 +CPU UTILIZATION: 23.878 / 28 ----------------------------------------- @@ -434,19 +434,19 @@ CPU UTILIZATION: 23.702 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 11 assigned | 11 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.433s -user 0m21.138s -sys 0m14.198s +real 0m1.436s +user 0m21.185s +sys 0m14.403s -CPU UTILIZATION: 24.658 / 28 +CPU UTILIZATION: 24.782 / 28 ----------------------------------------- @@ -464,11 +464,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.437s -user 0m21.126s -sys 0m14.290s +real 0m1.417s +user 0m21.442s +sys 0m14.532s -CPU UTILIZATION: 24.645 / 28 +CPU UTILIZATION: 25.387 / 28 ----------------------------------------- @@ -477,19 +477,19 @@ CPU UTILIZATION: 24.645 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 383 assigned | 383 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.460s -user 0m22.311s -sys 0m14.762s +real 0m1.458s +user 0m22.228s +sys 0m14.858s -CPU UTILIZATION: 25.392 / 28 +CPU UTILIZATION: 25.436 / 28 ----------------------------------------- @@ -498,20 +498,20 @@ CPU UTILIZATION: 25.392 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m1.457s -user 0m22.187s -sys 0m14.840s +real 0m1.462s +user 0m22.285s +sys 0m14.909s -CPU UTILIZATION: 25.413 / 28 +CPU UTILIZATION: 25.440 / 28 ----------------------------------------- @@ -520,19 +520,19 @@ CPU UTILIZATION: 25.413 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.133s -user 0m6.362s -sys 0m20.379s +real 0m1.135s +user 0m6.359s +sys 0m20.558s -CPU UTILIZATION: 23.601 / 28 +CPU UTILIZATION: 23.715 / 28 ----------------------------------------- @@ -550,11 +550,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.128s -user 0m6.202s -sys 0m20.552s +real 0m1.132s +user 0m6.263s +sys 0m20.681s -CPU UTILIZATION: 23.718 / 28 +CPU UTILIZATION: 23.802 / 28 ----------------------------------------- @@ -563,19 +563,19 @@ CPU UTILIZATION: 23.718 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.131s -user 0m6.421s -sys 0m20.565s +real 0m1.135s +user 0m6.565s +sys 0m20.612s -CPU UTILIZATION: 23.860 / 28 +CPU UTILIZATION: 23.944 / 28 ----------------------------------------- @@ -584,20 +584,20 @@ CPU UTILIZATION: 23.860 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 381 assigned | 383 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 0 -real 0m1.129s -user 0m6.388s -sys 0m20.579s +real 0m1.133s +user 0m6.303s +sys 0m20.872s -CPU UTILIZATION: 23.885 / 28 +CPU UTILIZATION: 23.984 / 28 ----------------------------------------- @@ -606,19 +606,19 @@ CPU UTILIZATION: 23.885 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.198s -user 0m6.420s -sys 0m22.155s +real 0m1.205s +user 0m6.522s +sys 0m22.251s -CPU UTILIZATION: 23.852 / 28 +CPU UTILIZATION: 23.878 / 28 ----------------------------------------- @@ -636,11 +636,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.205s -user 0m6.400s -sys 0m22.258s +real 0m1.211s +user 0m6.614s +sys 0m22.225s -CPU UTILIZATION: 23.782 / 28 +CPU UTILIZATION: 23.814 / 28 ----------------------------------------- @@ -649,19 +649,19 @@ CPU UTILIZATION: 23.782 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 382 processed | 0 I stole | 2 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.199s -user 0m6.416s -sys 0m22.344s +real 0m1.209s +user 0m6.700s +sys 0m22.313s -CPU UTILIZATION: 23.986 / 28 +CPU UTILIZATION: 23.997 / 28 ----------------------------------------- @@ -670,18 +670,18 @@ CPU UTILIZATION: 23.986 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 383 processed | 2 I stole | 0 stolen from me -Node 2 (Phys 2): 384 assigned | 382 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 385 assigned | 384 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 384 processed | 3 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= 25555 -real 0m1.201s -user 0m6.462s -sys 0m22.423s +real 0m1.209s +user 0m6.681s +sys 0m22.396s CPU UTILIZATION: 24.050 / 28 @@ -700,11 +700,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.890s -user 0m25.387s -sys 0m21.697s +real 0m1.894s +user 0m25.454s +sys 0m21.817s -CPU UTILIZATION: 24.912 / 28 +CPU UTILIZATION: 24.958 / 28 ----------------------------------------- @@ -722,11 +722,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.894s -user 0m25.111s -sys 0m22.089s +real 0m1.908s +user 0m25.246s +sys 0m22.081s -CPU UTILIZATION: 24.920 / 28 +CPU UTILIZATION: 24.804 / 28 ----------------------------------------- @@ -735,19 +735,19 @@ CPU UTILIZATION: 24.920 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.894s -user 0m25.392s -sys 0m21.974s +real 0m1.902s +user 0m25.708s +sys 0m21.907s -CPU UTILIZATION: 25.008 / 28 +CPU UTILIZATION: 25.034 / 28 ----------------------------------------- @@ -756,20 +756,20 @@ CPU UTILIZATION: 25.008 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.900s -user 0m25.371s -sys 0m22.093s +real 0m1.899s +user 0m25.396s +sys 0m22.314s -CPU UTILIZATION: 24.981 / 28 +CPU UTILIZATION: 25.123 / 28 ----------------------------------------- @@ -786,11 +786,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.663s -user 0m1.546s -sys 0m13.818s +real 0m0.661s +user 0m1.582s +sys 0m13.874s -CPU UTILIZATION: 23.173 / 28 +CPU UTILIZATION: 23.382 / 28 ----------------------------------------- @@ -808,11 +808,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.662s -user 0m1.574s -sys 0m13.831s +real 0m0.663s +user 0m1.618s +sys 0m13.822s -CPU UTILIZATION: 23.270 / 28 +CPU UTILIZATION: 23.288 / 28 ----------------------------------------- @@ -821,19 +821,19 @@ CPU UTILIZATION: 23.270 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 387 assigned | 384 processed | 1 I stole | 4 stolen from me -Node 1 (Phys 1): 387 assigned | 384 processed | 0 I stole | 3 stolen from me -Node 2 (Phys 2): 375 assigned | 380 processed | 5 I stole | 0 stolen from me -Node 3 (Phys 3): 378 assigned | 379 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 380 assigned | 383 processed | 5 I stole | 2 stolen from me +Node 1 (Phys 1): 385 assigned | 387 processed | 4 I stole | 2 stolen from me +Node 2 (Phys 2): 382 assigned | 379 processed | 2 I stole | 5 stolen from me +Node 3 (Phys 3): 380 assigned | 378 processed | 2 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 7 chunks (0.5%) +Total Cross-Socket Traffic: 13 chunks (0.9%) ================================================================= -real 0m0.711s -user 0m2.467s -sys 0m14.176s +real 0m0.708s +user 0m2.456s +sys 0m14.219s -CPU UTILIZATION: 23.407 / 28 +CPU UTILIZATION: 23.552 / 28 ----------------------------------------- @@ -842,20 +842,20 @@ CPU UTILIZATION: 23.407 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 382 processed | 0 I stole | 2 stolen from me -Node 1 (Phys 1): 384 assigned | 385 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 377 assigned | 380 processed | 8 I stole | 5 stolen from me +Node 1 (Phys 1): 382 assigned | 379 processed | 2 I stole | 5 stolen from me +Node 2 (Phys 2): 382 assigned | 384 processed | 8 I stole | 6 stolen from me +Node 3 (Phys 3): 386 assigned | 384 processed | 2 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.3%) +Total Cross-Socket Traffic: 20 chunks (1.3%) ================================================================= 0 -real 0m0.705s -user 0m2.457s -sys 0m14.144s +real 0m0.706s +user 0m2.494s +sys 0m14.213s -CPU UTILIZATION: 23.547 / 28 +CPU UTILIZATION: 23.664 / 28 ----------------------------------------- @@ -864,19 +864,19 @@ CPU UTILIZATION: 23.547 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 13 assigned | 12 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 11 assigned | 12 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (2.0%) ================================================================= real 0m0.704s -user 0m2.315s -sys 0m14.140s +user 0m2.406s +sys 0m14.151s -CPU UTILIZATION: 23.373 / 28 +CPU UTILIZATION: 23.518 / 28 ----------------------------------------- @@ -894,11 +894,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m0.706s -user 0m2.313s -sys 0m14.178s +real 0m0.700s +user 0m2.389s +sys 0m14.174s -CPU UTILIZATION: 23.358 / 28 +CPU UTILIZATION: 23.661 / 28 ----------------------------------------- @@ -907,19 +907,19 @@ CPU UTILIZATION: 23.358 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 384 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 377 assigned | 378 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 385 assigned | 385 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 377 assigned | 377 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.749s -user 0m3.192s -sys 0m14.559s +real 0m0.752s +user 0m3.220s +sys 0m14.636s -CPU UTILIZATION: 23.699 / 28 +CPU UTILIZATION: 23.744 / 28 ----------------------------------------- @@ -928,20 +928,20 @@ CPU UTILIZATION: 23.699 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 391 assigned | 385 processed | 1 I stole | 7 stolen from me -Node 1 (Phys 1): 382 assigned | 381 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 374 assigned | 381 processed | 7 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 3 I stole | 3 stolen from me +Node 0 (Phys 0): 392 assigned | 388 processed | 1 I stole | 5 stolen from me +Node 1 (Phys 1): 383 assigned | 384 processed | 3 I stole | 2 stolen from me +Node 2 (Phys 2): 380 assigned | 379 processed | 2 I stole | 3 stolen from me +Node 3 (Phys 3): 372 assigned | 376 processed | 4 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 12 chunks (0.8%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= 5965 -real 0m0.750s -user 0m3.283s +real 0m0.749s +user 0m3.367s sys 0m14.531s -CPU UTILIZATION: 23.752 / 28 +CPU UTILIZATION: 23.895 / 28 ----------------------------------------- @@ -959,10 +959,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m1.410s -user 0m21.463s -sys 0m14.302s +user 0m21.459s +sys 0m14.479s -CPU UTILIZATION: 25.365 / 28 +CPU UTILIZATION: 25.487 / 28 ----------------------------------------- @@ -980,11 +980,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.411s -user 0m21.567s -sys 0m14.341s +real 0m1.414s +user 0m21.468s +sys 0m14.509s -CPU UTILIZATION: 25.448 / 28 +CPU UTILIZATION: 25.443 / 28 ----------------------------------------- @@ -993,19 +993,19 @@ CPU UTILIZATION: 25.448 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.462s -user 0m22.278s -sys 0m14.732s +real 0m1.457s +user 0m22.238s +sys 0m14.845s -CPU UTILIZATION: 25.314 / 28 +CPU UTILIZATION: 25.451 / 28 ----------------------------------------- @@ -1014,20 +1014,20 @@ CPU UTILIZATION: 25.314 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 383 assigned | 384 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 100000000 -real 0m1.461s -user 0m22.282s -sys 0m14.833s +real 0m1.462s +user 0m22.216s +sys 0m14.903s -CPU UTILIZATION: 25.403 / 28 +CPU UTILIZATION: 25.389 / 28 ----------------------------------------- @@ -1044,11 +1044,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.100s -user 0m5.865s -sys 0m20.159s +real 0m1.107s +user 0m6.045s +sys 0m20.157s -CPU UTILIZATION: 23.658 / 28 +CPU UTILIZATION: 23.669 / 28 ----------------------------------------- @@ -1066,11 +1066,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.107s -user 0m6.009s -sys 0m20.002s +real 0m1.103s +user 0m6.007s +sys 0m20.178s -CPU UTILIZATION: 23.496 / 28 +CPU UTILIZATION: 23.739 / 28 ----------------------------------------- @@ -1079,19 +1079,19 @@ CPU UTILIZATION: 23.496 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.112s -user 0m5.949s -sys 0m20.200s +real 0m1.109s +user 0m6.081s +sys 0m20.387s -CPU UTILIZATION: 23.515 / 28 +CPU UTILIZATION: 23.866 / 28 ----------------------------------------- @@ -1100,20 +1100,20 @@ CPU UTILIZATION: 23.515 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.101s -user 0m6.032s -sys 0m20.187s +real 0m1.108s +user 0m6.057s +sys 0m20.410s -CPU UTILIZATION: 23.813 / 28 +CPU UTILIZATION: 23.887 / 28 ----------------------------------------- @@ -1131,10 +1131,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m1.166s -user 0m5.933s -sys 0m21.689s +user 0m6.119s +sys 0m21.686s -CPU UTILIZATION: 23.689 / 28 +CPU UTILIZATION: 23.846 / 28 ----------------------------------------- @@ -1152,11 +1152,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.166s -user 0m6.011s -sys 0m21.737s +real 0m1.174s +user 0m6.017s +sys 0m21.951s -CPU UTILIZATION: 23.797 / 28 +CPU UTILIZATION: 23.822 / 28 ----------------------------------------- @@ -1165,19 +1165,19 @@ CPU UTILIZATION: 23.797 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.169s -user 0m6.084s -sys 0m21.782s +real 0m1.165s +user 0m6.255s +sys 0m21.818s -CPU UTILIZATION: 23.837 / 28 +CPU UTILIZATION: 24.096 / 28 ----------------------------------------- @@ -1186,20 +1186,20 @@ CPU UTILIZATION: 23.837 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 382 processed | 2 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 1 I stole | 2 stolen from me +Node 1 (Phys 1): 382 assigned | 383 processed | 2 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= 25555 -real 0m1.173s -user 0m6.109s -sys 0m21.938s +real 0m1.176s +user 0m6.358s +sys 0m21.855s -CPU UTILIZATION: 23.910 / 28 +CPU UTILIZATION: 23.990 / 28 ----------------------------------------- @@ -1216,11 +1216,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.855s -user 0m24.785s -sys 0m21.351s +real 0m1.859s +user 0m24.940s +sys 0m21.420s -CPU UTILIZATION: 24.871 / 28 +CPU UTILIZATION: 24.938 / 28 ----------------------------------------- @@ -1229,20 +1229,20 @@ CPU UTILIZATION: 24.871 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.865s -user 0m24.712s -sys 0m21.590s +real 0m1.872s +user 0m24.875s +sys 0m21.620s -CPU UTILIZATION: 24.826 / 28 +CPU UTILIZATION: 24.837 / 28 ----------------------------------------- @@ -1251,19 +1251,19 @@ CPU UTILIZATION: 24.826 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 384 processed | 3 I stole | 0 stolen from me +Node 3 (Phys 3): 383 assigned | 381 processed | 0 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= -real 0m1.857s -user 0m24.939s -sys 0m21.501s +real 0m1.863s +user 0m25.102s +sys 0m21.582s -CPU UTILIZATION: 25.008 / 28 +CPU UTILIZATION: 25.058 / 28 ----------------------------------------- @@ -1272,20 +1272,20 @@ CPU UTILIZATION: 25.008 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 380 assigned | 381 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m1.863s -user 0m24.828s -sys 0m21.800s +real 0m1.870s +user 0m25.268s +sys 0m21.587s -CPU UTILIZATION: 25.028 / 28 +CPU UTILIZATION: 25.056 / 28 ----------------------------------------- @@ -1302,11 +1302,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.653s -user 0m1.507s -sys 0m13.760s +real 0m0.657s +user 0m1.497s +sys 0m13.790s -CPU UTILIZATION: 23.379 / 28 +CPU UTILIZATION: 23.267 / 28 ----------------------------------------- @@ -1324,11 +1324,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.658s -user 0m1.548s -sys 0m13.705s +real 0m0.669s +user 0m1.583s +sys 0m13.755s -CPU UTILIZATION: 23.180 / 28 +CPU UTILIZATION: 22.926 / 28 ----------------------------------------- @@ -1337,19 +1337,19 @@ CPU UTILIZATION: 23.180 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 383 assigned | 381 processed | 0 I stole | 2 stolen from me +Node 0 (Phys 0): 382 assigned | 383 processed | 4 I stole | 3 stolen from me +Node 1 (Phys 1): 386 assigned | 384 processed | 3 I stole | 5 stolen from me +Node 2 (Phys 2): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 377 assigned | 379 processed | 3 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.3%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= -real 0m0.700s -user 0m2.378s -sys 0m14.038s +real 0m0.701s +user 0m2.422s +sys 0m14.123s -CPU UTILIZATION: 23.451 / 28 +CPU UTILIZATION: 23.601 / 28 ----------------------------------------- @@ -1358,20 +1358,20 @@ CPU UTILIZATION: 23.451 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 384 processed | 0 I stole | 2 stolen from me -Node 1 (Phys 1): 386 assigned | 384 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 376 assigned | 378 processed | 4 I stole | 2 stolen from me -Node 3 (Phys 3): 379 assigned | 381 processed | 3 I stole | 1 stolen from me +Node 0 (Phys 0): 384 assigned | 386 processed | 4 I stole | 2 stolen from me +Node 1 (Phys 1): 380 assigned | 380 processed | 4 I stole | 4 stolen from me +Node 2 (Phys 2): 379 assigned | 379 processed | 3 I stole | 3 stolen from me +Node 3 (Phys 3): 384 assigned | 382 processed | 1 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 7 chunks (0.5%) +Total Cross-Socket Traffic: 12 chunks (0.8%) ================================================================= 0 -real 0m0.701s -user 0m2.340s -sys 0m14.139s +real 0m0.695s +user 0m2.378s +sys 0m14.151s -CPU UTILIZATION: 23.507 / 28 +CPU UTILIZATION: 23.782 / 28 ----------------------------------------- @@ -1388,11 +1388,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.695s -user 0m2.244s -sys 0m13.978s +real 0m0.693s +user 0m2.276s +sys 0m14.024s -CPU UTILIZATION: 23.341 / 28 +CPU UTILIZATION: 23.520 / 28 ----------------------------------------- @@ -1410,11 +1410,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m0.717s -user 0m2.151s -sys 0m13.976s +real 0m0.716s +user 0m2.201s +sys 0m14.021s -CPU UTILIZATION: 22.492 / 28 +CPU UTILIZATION: 22.656 / 28 ----------------------------------------- @@ -1423,19 +1423,19 @@ CPU UTILIZATION: 22.492 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 385 processed | 4 I stole | 1 stolen from me -Node 2 (Phys 2): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 377 processed | 0 I stole | 4 stolen from me +Node 0 (Phys 0): 386 assigned | 383 processed | 1 I stole | 4 stolen from me +Node 1 (Phys 1): 385 assigned | 379 processed | 1 I stole | 7 stolen from me +Node 2 (Phys 2): 381 assigned | 384 processed | 4 I stole | 1 stolen from me +Node 3 (Phys 3): 375 assigned | 381 processed | 6 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.3%) +Total Cross-Socket Traffic: 12 chunks (0.8%) ================================================================= real 0m0.738s -user 0m3.108s -sys 0m14.341s +user 0m3.143s +sys 0m14.396s -CPU UTILIZATION: 23.643 / 28 +CPU UTILIZATION: 23.765 / 28 ----------------------------------------- @@ -1444,20 +1444,20 @@ CPU UTILIZATION: 23.643 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 384 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 379 assigned | 378 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 381 assigned | 382 processed | 5 I stole | 4 stolen from me +Node 1 (Phys 1): 385 assigned | 382 processed | 2 I stole | 5 stolen from me +Node 2 (Phys 2): 381 assigned | 381 processed | 3 I stole | 3 stolen from me +Node 3 (Phys 3): 380 assigned | 382 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.2%) +Total Cross-Socket Traffic: 12 chunks (0.8%) ================================================================= 5965 -real 0m0.757s -user 0m3.087s -sys 0m14.352s +real 0m0.764s +user 0m3.119s +sys 0m14.484s -CPU UTILIZATION: 23.036 / 28 +CPU UTILIZATION: 23.040 / 28 ----------------------------------------- @@ -1466,19 +1466,19 @@ CPU UTILIZATION: 23.036 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.403s -user 0m21.436s -sys 0m14.156s +real 0m1.396s +user 0m21.254s +sys 0m14.273s -CPU UTILIZATION: 25.368 / 28 +CPU UTILIZATION: 25.449 / 28 ----------------------------------------- @@ -1487,20 +1487,20 @@ CPU UTILIZATION: 25.368 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.409s -user 0m20.878s -sys 0m14.137s +real 0m1.422s +user 0m20.778s +sys 0m14.273s -CPU UTILIZATION: 24.850 / 28 +CPU UTILIZATION: 24.649 / 28 ----------------------------------------- @@ -1509,19 +1509,19 @@ CPU UTILIZATION: 24.850 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 385 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 385 assigned | 384 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 378 assigned | 381 processed | 3 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 377 processed | 0 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= -real 0m1.441s -user 0m22.215s -sys 0m14.629s +real 0m1.444s +user 0m22.146s +sys 0m14.673s -CPU UTILIZATION: 25.568 / 28 +CPU UTILIZATION: 25.497 / 28 ----------------------------------------- @@ -1530,20 +1530,20 @@ CPU UTILIZATION: 25.568 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 378 assigned | 378 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.455s -user 0m21.657s -sys 0m14.659s +real 0m1.461s +user 0m21.724s +sys 0m14.798s -CPU UTILIZATION: 24.959 / 28 +CPU UTILIZATION: 24.997 / 28 ----------------------------------------- @@ -1552,19 +1552,19 @@ CPU UTILIZATION: 24.959 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.361s -user 0m34.788s -sys 0m0.664s +real 0m1.353s +user 0m34.614s +sys 0m0.721s -CPU UTILIZATION: 26.048 / 28 +CPU UTILIZATION: 26.116 / 28 ----------------------------------------- @@ -1573,8 +1573,8 @@ CPU UTILIZATION: 26.048 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -1582,11 +1582,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.361s -user 0m34.637s -sys 0m0.701s +real 0m1.368s +user 0m34.747s +sys 0m0.675s -CPU UTILIZATION: 25.964 / 28 +CPU UTILIZATION: 25.893 / 28 ----------------------------------------- @@ -1595,19 +1595,19 @@ CPU UTILIZATION: 25.964 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 379 assigned | 380 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 390 assigned | 390 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 374 assigned | 374 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 377 assigned | 377 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 388 assigned | 388 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.368s -user 0m34.769s -sys 0m0.881s +real 0m1.384s +user 0m34.797s +sys 0m0.845s -CPU UTILIZATION: 26.059 / 28 +CPU UTILIZATION: 25.752 / 28 ----------------------------------------- @@ -1616,20 +1616,20 @@ CPU UTILIZATION: 26.059 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 371 assigned | 371 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 387 assigned | 387 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 393 assigned | 392 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 366 assigned | 366 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 0 -real 0m1.354s -user 0m34.808s -sys 0m0.767s +real 0m1.391s +user 0m35.114s +sys 0m0.987s -CPU UTILIZATION: 26.274 / 28 +CPU UTILIZATION: 25.953 / 28 ----------------------------------------- @@ -1638,19 +1638,19 @@ CPU UTILIZATION: 26.274 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.359s -user 0m34.534s -sys 0m0.741s +real 0m1.398s +user 0m34.483s +sys 0m0.762s -CPU UTILIZATION: 25.956 / 28 +CPU UTILIZATION: 25.211 / 28 ----------------------------------------- @@ -1668,11 +1668,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.371s -user 0m34.548s -sys 0m0.786s +real 0m1.405s +user 0m34.119s +sys 0m0.851s -CPU UTILIZATION: 25.772 / 28 +CPU UTILIZATION: 24.889 / 28 ----------------------------------------- @@ -1681,19 +1681,19 @@ CPU UTILIZATION: 25.772 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 391 assigned | 391 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 363 assigned | 363 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 373 assigned | 373 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 389 assigned | 389 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.363s -user 0m34.712s -sys 0m0.927s +real 0m1.371s +user 0m34.751s +sys 0m1.008s -CPU UTILIZATION: 26.147 / 28 +CPU UTILIZATION: 26.082 / 28 ----------------------------------------- @@ -1702,20 +1702,20 @@ CPU UTILIZATION: 26.147 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 388 assigned | 389 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 390 assigned | 389 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 367 assigned | 367 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 377 assigned | 376 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 389 assigned | 389 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 385 assigned | 386 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 376 assigned | 376 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 25555 -real 0m1.364s -user 0m34.875s -sys 0m0.915s +real 0m1.370s +user 0m34.854s +sys 0m1.006s -CPU UTILIZATION: 26.239 / 28 +CPU UTILIZATION: 26.175 / 28 ----------------------------------------- @@ -1732,11 +1732,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.364s -user 0m34.701s -sys 0m0.765s +real 0m1.366s +user 0m34.838s +sys 0m0.801s -CPU UTILIZATION: 26.001 / 28 +CPU UTILIZATION: 26.090 / 28 ----------------------------------------- @@ -1754,11 +1754,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.367s -user 0m34.825s -sys 0m0.830s +real 0m1.375s +user 0m34.875s +sys 0m0.809s -CPU UTILIZATION: 26.082 / 28 +CPU UTILIZATION: 25.952 / 28 ----------------------------------------- @@ -1767,19 +1767,19 @@ CPU UTILIZATION: 26.082 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 387 assigned | 387 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 373 assigned | 373 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 385 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 388 assigned | 387 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 374 assigned | 374 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m1.368s -user 0m34.920s -sys 0m0.896s +real 0m1.372s +user 0m34.910s +sys 0m0.925s -CPU UTILIZATION: 26.181 / 28 +CPU UTILIZATION: 26.118 / 28 ----------------------------------------- @@ -1788,20 +1788,20 @@ CPU UTILIZATION: 26.181 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 372 assigned | 372 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 394 assigned | 394 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 375 assigned | 375 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 388 assigned | 389 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 394 assigned | 393 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 366 assigned | 365 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 25555 -real 0m1.370s -user 0m34.968s -sys 0m0.931s +real 0m1.378s +user 0m35.072s +sys 0m1.015s -CPU UTILIZATION: 26.203 / 28 +CPU UTILIZATION: 26.187 / 28 ----------------------------------------- @@ -1818,11 +1818,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.622s -user 0m41.732s -sys 0m0.490s +real 0m1.615s +user 0m41.573s +sys 0m0.503s -CPU UTILIZATION: 26.030 / 28 +CPU UTILIZATION: 26.053 / 28 ----------------------------------------- @@ -1831,20 +1831,20 @@ CPU UTILIZATION: 26.030 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.612s -user 0m41.482s -sys 0m0.517s +real 0m1.613s +user 0m41.597s +sys 0m0.483s -CPU UTILIZATION: 26.053 / 28 +CPU UTILIZATION: 26.088 / 28 ----------------------------------------- @@ -1853,19 +1853,19 @@ CPU UTILIZATION: 26.053 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 387 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 378 assigned | 379 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 377 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 388 assigned | 388 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 387 assigned | 387 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 367 assigned | 367 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m1.706s -user 0m44.221s -sys 0m0.761s +user 0m44.095s +sys 0m0.712s -CPU UTILIZATION: 26.366 / 28 +CPU UTILIZATION: 26.264 / 28 ----------------------------------------- @@ -1874,20 +1874,20 @@ CPU UTILIZATION: 26.366 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 372 assigned | 371 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 391 assigned | 390 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 374 assigned | 375 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 0 real 0m1.704s -user 0m44.165s -sys 0m0.737s +user 0m43.906s +sys 0m0.845s -CPU UTILIZATION: 26.350 / 28 +CPU UTILIZATION: 26.262 / 28 ----------------------------------------- @@ -1904,11 +1904,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.617s -user 0m41.605s -sys 0m0.476s +real 0m1.624s +user 0m41.379s +sys 0m0.552s -CPU UTILIZATION: 26.024 / 28 +CPU UTILIZATION: 25.819 / 28 ----------------------------------------- @@ -1926,11 +1926,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m1.614s -user 0m41.286s -sys 0m0.578s +real 0m1.626s +user 0m41.528s +sys 0m0.522s -CPU UTILIZATION: 25.938 / 28 +CPU UTILIZATION: 25.861 / 28 ----------------------------------------- @@ -1939,19 +1939,19 @@ CPU UTILIZATION: 25.938 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 378 assigned | 377 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 396 assigned | 395 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 374 assigned | 374 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 378 assigned | 376 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 379 assigned | 382 processed | 3 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= -real 0m1.713s -user 0m44.078s -sys 0m0.772s +real 0m1.716s +user 0m44.080s +sys 0m0.785s -CPU UTILIZATION: 26.182 / 28 +CPU UTILIZATION: 26.145 / 28 ----------------------------------------- @@ -1960,20 +1960,20 @@ CPU UTILIZATION: 26.182 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 389 assigned | 389 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 366 assigned | 366 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 392 assigned | 392 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 391 assigned | 392 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 369 assigned | 368 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 386 assigned | 387 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 5965 -real 0m1.710s -user 0m44.256s -sys 0m0.748s +real 0m1.711s +user 0m44.022s +sys 0m0.823s -CPU UTILIZATION: 26.318 / 28 +CPU UTILIZATION: 26.209 / 28 ----------------------------------------- @@ -1982,19 +1982,19 @@ CPU UTILIZATION: 26.318 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.619s -user 0m41.472s -sys 0m0.515s +real 0m1.638s +user 0m41.746s +sys 0m0.499s -CPU UTILIZATION: 25.933 / 28 +CPU UTILIZATION: 25.790 / 28 ----------------------------------------- @@ -2012,11 +2012,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m1.637s -user 0m41.625s -sys 0m0.547s +real 0m1.640s +user 0m41.607s +sys 0m0.534s -CPU UTILIZATION: 25.761 / 28 +CPU UTILIZATION: 25.695 / 28 ----------------------------------------- @@ -2025,19 +2025,19 @@ CPU UTILIZATION: 25.761 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 370 assigned | 370 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 389 assigned | 389 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 372 assigned | 372 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 396 assigned | 396 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 373 assigned | 374 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 390 assigned | 392 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 391 assigned | 389 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 373 assigned | 372 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= -real 0m1.710s -user 0m44.173s -sys 0m0.812s +real 0m1.721s +user 0m44.157s +sys 0m0.833s -CPU UTILIZATION: 26.307 / 28 +CPU UTILIZATION: 26.141 / 28 ----------------------------------------- @@ -2046,20 +2046,20 @@ CPU UTILIZATION: 26.307 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 395 assigned | 395 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 371 assigned | 371 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 390 assigned | 391 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 380 assigned | 382 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 393 assigned | 392 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 371 assigned | 370 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 5965 -real 0m1.706s -user 0m44.024s -sys 0m0.796s +real 0m1.713s +user 0m44.138s +sys 0m0.819s -CPU UTILIZATION: 26.271 / 28 +CPU UTILIZATION: 26.244 / 28 ----------------------------------------- @@ -2068,19 +2068,19 @@ CPU UTILIZATION: 26.271 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 14 assigned | 14 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.166s -user 0m1.635s -sys 0m0.729s +real 0m0.171s +user 0m1.785s +sys 0m0.762s -CPU UTILIZATION: 14.240 / 28 +CPU UTILIZATION: 14.894 / 28 ----------------------------------------- @@ -2089,20 +2089,20 @@ CPU UTILIZATION: 14.240 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 14 assigned | 14 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 10 assigned | 10 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.163s -user 0m1.692s -sys 0m0.727s +real 0m0.174s +user 0m1.726s +sys 0m0.738s -CPU UTILIZATION: 14.840 / 28 +CPU UTILIZATION: 14.160 / 28 ----------------------------------------- @@ -2111,19 +2111,19 @@ CPU UTILIZATION: 14.840 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 410 assigned | 402 processed | 25 I stole | 33 stolen from me -Node 1 (Phys 1): 360 assigned | 360 processed | 27 I stole | 27 stolen from me -Node 2 (Phys 2): 371 assigned | 381 processed | 35 I stole | 25 stolen from me -Node 3 (Phys 3): 386 assigned | 384 processed | 20 I stole | 22 stolen from me +Node 0 (Phys 0): 402 assigned | 419 processed | 34 I stole | 17 stolen from me +Node 1 (Phys 1): 368 assigned | 364 processed | 19 I stole | 23 stolen from me +Node 2 (Phys 2): 396 assigned | 404 processed | 31 I stole | 23 stolen from me +Node 3 (Phys 3): 361 assigned | 340 processed | 9 I stole | 30 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 107 chunks (7.0%) +Total Cross-Socket Traffic: 93 chunks (6.1%) ================================================================= -real 0m0.180s -user 0m1.755s -sys 0m0.871s +real 0m0.192s +user 0m1.844s +sys 0m0.911s -CPU UTILIZATION: 14.588 / 28 +CPU UTILIZATION: 14.348 / 28 ----------------------------------------- @@ -2132,20 +2132,20 @@ CPU UTILIZATION: 14.588 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 361 processed | 29 I stole | 50 stolen from me -Node 1 (Phys 1): 361 assigned | 357 processed | 25 I stole | 29 stolen from me -Node 2 (Phys 2): 402 assigned | 420 processed | 36 I stole | 18 stolen from me -Node 3 (Phys 3): 382 assigned | 389 processed | 35 I stole | 28 stolen from me +Node 0 (Phys 0): 396 assigned | 399 processed | 21 I stole | 18 stolen from me +Node 1 (Phys 1): 369 assigned | 353 processed | 19 I stole | 35 stolen from me +Node 2 (Phys 2): 398 assigned | 404 processed | 21 I stole | 15 stolen from me +Node 3 (Phys 3): 364 assigned | 371 processed | 28 I stole | 21 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 125 chunks (8.2%) +Total Cross-Socket Traffic: 89 chunks (5.8%) ================================================================= 0 -real 0m0.181s -user 0m1.785s -sys 0m0.892s +real 0m0.184s +user 0m1.820s +sys 0m0.935s -CPU UTILIZATION: 14.790 / 28 +CPU UTILIZATION: 14.972 / 28 ----------------------------------------- @@ -2162,11 +2162,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.746s -user 0m9.155s -sys 0m7.493s +real 0m0.755s +user 0m9.119s +sys 0m7.691s -CPU UTILIZATION: 22.316 / 28 +CPU UTILIZATION: 22.264 / 28 ----------------------------------------- @@ -2184,11 +2184,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.748s -user 0m9.060s -sys 0m7.655s +real 0m0.761s +user 0m9.173s +sys 0m7.735s -CPU UTILIZATION: 22.346 / 28 +CPU UTILIZATION: 22.218 / 28 ----------------------------------------- @@ -2197,19 +2197,19 @@ CPU UTILIZATION: 22.346 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 385 processed | 3 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 384 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 382 assigned | 381 processed | 0 I stole | 1 stolen from me Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.2%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m0.755s -user 0m9.131s -sys 0m7.750s +real 0m0.765s +user 0m9.211s +sys 0m7.805s -CPU UTILIZATION: 22.358 / 28 +CPU UTILIZATION: 22.243 / 28 ----------------------------------------- @@ -2218,20 +2218,20 @@ CPU UTILIZATION: 22.358 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m0.752s -user 0m9.074s -sys 0m7.892s +real 0m0.761s +user 0m9.290s +sys 0m7.869s -CPU UTILIZATION: 22.561 / 28 +CPU UTILIZATION: 22.547 / 28 ----------------------------------------- @@ -2249,10 +2249,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.738s -user 0m9.061s -sys 0m7.327s +user 0m9.119s +sys 0m7.333s -CPU UTILIZATION: 22.205 / 28 +CPU UTILIZATION: 22.292 / 28 ----------------------------------------- @@ -2270,11 +2270,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.742s -user 0m9.076s -sys 0m7.463s +real 0m0.749s +user 0m9.178s +sys 0m7.488s -CPU UTILIZATION: 22.289 / 28 +CPU UTILIZATION: 22.251 / 28 ----------------------------------------- @@ -2283,19 +2283,19 @@ CPU UTILIZATION: 22.289 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 378 assigned | 378 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 384 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 1 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m0.738s -user 0m9.050s -sys 0m7.523s +real 0m0.745s +user 0m9.230s +sys 0m7.429s -CPU UTILIZATION: 22.456 / 28 +CPU UTILIZATION: 22.361 / 28 ----------------------------------------- @@ -2304,20 +2304,20 @@ CPU UTILIZATION: 22.456 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 383 processed | 2 I stole | 0 stolen from me Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 379 assigned | 380 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 100000000 -real 0m0.745s -user 0m9.147s -sys 0m7.582s +real 0m0.748s +user 0m9.153s +sys 0m7.655s -CPU UTILIZATION: 22.455 / 28 +CPU UTILIZATION: 22.470 / 28 ----------------------------------------- @@ -2335,10 +2335,10 @@ Total Cross-Socket Traffic: 1 chunks (2.0%) ================================================================= real 0m0.112s -user 0m0.043s -sys 0m0.149s +user 0m0.039s +sys 0m0.156s -CPU UTILIZATION: 1.714 / 28 +CPU UTILIZATION: 1.741 / 28 ----------------------------------------- @@ -2356,11 +2356,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.118s -user 0m0.040s -sys 0m0.155s +real 0m0.125s +user 0m0.051s +sys 0m0.152s -CPU UTILIZATION: 1.652 / 28 +CPU UTILIZATION: 1.624 / 28 ----------------------------------------- @@ -2369,19 +2369,19 @@ CPU UTILIZATION: 1.652 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 378 processed | 0 I stole | 5 stolen from me -Node 1 (Phys 1): 385 assigned | 395 processed | 10 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 380 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 377 assigned | 374 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 391 assigned | 397 processed | 9 I stole | 3 stolen from me +Node 1 (Phys 1): 388 assigned | 388 processed | 4 I stole | 4 stolen from me +Node 2 (Phys 2): 376 assigned | 373 processed | 2 I stole | 5 stolen from me +Node 3 (Phys 3): 372 assigned | 369 processed | 2 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 10 chunks (0.7%) +Total Cross-Socket Traffic: 17 chunks (1.1%) ================================================================= -real 0m0.125s -user 0m0.226s -sys 0m0.252s +real 0m0.131s +user 0m0.247s +sys 0m0.269s -CPU UTILIZATION: 3.824 / 28 +CPU UTILIZATION: 3.938 / 28 ----------------------------------------- @@ -2390,20 +2390,20 @@ CPU UTILIZATION: 3.824 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 396 assigned | 409 processed | 14 I stole | 1 stolen from me -Node 1 (Phys 1): 388 assigned | 383 processed | 1 I stole | 6 stolen from me -Node 2 (Phys 2): 376 assigned | 372 processed | 1 I stole | 5 stolen from me -Node 3 (Phys 3): 367 assigned | 363 processed | 1 I stole | 5 stolen from me +Node 0 (Phys 0): 385 assigned | 385 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (1.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 0 -real 0m0.122s -user 0m0.238s -sys 0m0.242s +real 0m0.127s +user 0m0.260s +sys 0m0.238s -CPU UTILIZATION: 3.934 / 28 +CPU UTILIZATION: 3.921 / 28 ----------------------------------------- @@ -2420,11 +2420,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.113s -user 0m0.097s -sys 0m0.221s +real 0m0.121s +user 0m0.092s +sys 0m0.246s -CPU UTILIZATION: 2.814 / 28 +CPU UTILIZATION: 2.793 / 28 ----------------------------------------- @@ -2442,11 +2442,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.121s -user 0m0.093s -sys 0m0.272s +real 0m0.116s +user 0m0.108s +sys 0m0.263s -CPU UTILIZATION: 3.016 / 28 +CPU UTILIZATION: 3.198 / 28 ----------------------------------------- @@ -2455,19 +2455,19 @@ CPU UTILIZATION: 3.016 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 385 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 381 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 372 assigned | 373 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 381 processed | 3 I stole | 4 stolen from me +Node 1 (Phys 1): 386 assigned | 386 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 380 processed | 3 I stole | 4 stolen from me +Node 3 (Phys 3): 378 assigned | 380 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 9 chunks (0.6%) ================================================================= -real 0m0.150s -user 0m0.563s -sys 0m0.598s +real 0m0.152s +user 0m0.584s +sys 0m0.583s -CPU UTILIZATION: 7.740 / 28 +CPU UTILIZATION: 7.677 / 28 ----------------------------------------- @@ -2476,20 +2476,20 @@ CPU UTILIZATION: 7.740 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 388 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 380 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 1 I stole | 2 stolen from me -Node 3 (Phys 3): 378 assigned | 378 processed | 2 I stole | 2 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 3 I stole | 4 stolen from me +Node 1 (Phys 1): 380 assigned | 381 processed | 3 I stole | 2 stolen from me +Node 2 (Phys 2): 379 assigned | 379 processed | 4 I stole | 4 stolen from me +Node 3 (Phys 3): 384 assigned | 384 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 6 chunks (0.4%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= 100000000 -real 0m0.151s -user 0m0.586s -sys 0m0.614s +real 0m0.153s +user 0m0.590s +sys 0m0.630s -CPU UTILIZATION: 7.947 / 28 +CPU UTILIZATION: 7.973 / 28 ----------------------------------------- @@ -2506,11 +2506,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.113s -user 0m0.098s -sys 0m0.221s +real 0m0.110s +user 0m0.105s +sys 0m0.220s -CPU UTILIZATION: 2.823 / 28 +CPU UTILIZATION: 2.954 / 28 ----------------------------------------- @@ -2528,11 +2528,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.119s -user 0m0.113s -sys 0m0.236s +real 0m0.115s +user 0m0.105s +sys 0m0.273s -CPU UTILIZATION: 2.932 / 28 +CPU UTILIZATION: 3.286 / 28 ----------------------------------------- @@ -2541,19 +2541,19 @@ CPU UTILIZATION: 2.932 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 384 processed | 2 I stole | 4 stolen from me -Node 1 (Phys 1): 383 assigned | 385 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 378 assigned | 379 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 379 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 381 assigned | 384 processed | 3 I stole | 0 stolen from me +Node 1 (Phys 1): 379 assigned | 379 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 383 assigned | 381 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 384 assigned | 383 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.6%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= real 0m0.150s -user 0m0.577s -sys 0m0.546s +user 0m0.556s +sys 0m0.563s -CPU UTILIZATION: 7.486 / 28 +CPU UTILIZATION: 7.460 / 28 ----------------------------------------- @@ -2562,20 +2562,20 @@ CPU UTILIZATION: 7.486 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 384 processed | 2 I stole | 4 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 383 assigned | 384 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 376 assigned | 376 processed | 2 I stole | 2 stolen from me +Node 0 (Phys 0): 381 assigned | 383 processed | 4 I stole | 2 stolen from me +Node 1 (Phys 1): 383 assigned | 385 processed | 3 I stole | 1 stolen from me +Node 2 (Phys 2): 378 assigned | 378 processed | 3 I stole | 3 stolen from me +Node 3 (Phys 3): 385 assigned | 381 processed | 0 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 8 chunks (0.5%) +Total Cross-Socket Traffic: 10 chunks (0.7%) ================================================================= 100000000 real 0m0.149s -user 0m0.550s -sys 0m0.617s +user 0m0.565s +sys 0m0.610s -CPU UTILIZATION: 7.832 / 28 +CPU UTILIZATION: 7.885 / 28 ----------------------------------------- @@ -2592,11 +2592,11 @@ Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.165s -user 0m1.605s -sys 0m0.633s +real 0m0.173s +user 0m1.608s +sys 0m0.684s -CPU UTILIZATION: 13.563 / 28 +CPU UTILIZATION: 13.248 / 28 ----------------------------------------- @@ -2606,19 +2606,19 @@ CPU UTILIZATION: 13.563 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.164s -user 0m1.520s -sys 0m0.725s +real 0m0.173s +user 0m1.626s +sys 0m0.662s -CPU UTILIZATION: 13.689 / 28 +CPU UTILIZATION: 13.225 / 28 ----------------------------------------- @@ -2627,19 +2627,19 @@ CPU UTILIZATION: 13.689 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 383 processed | 22 I stole | 25 stolen from me -Node 1 (Phys 1): 392 assigned | 397 processed | 23 I stole | 18 stolen from me -Node 2 (Phys 2): 389 assigned | 391 processed | 21 I stole | 19 stolen from me -Node 3 (Phys 3): 360 assigned | 356 processed | 16 I stole | 20 stolen from me +Node 0 (Phys 0): 424 assigned | 429 processed | 26 I stole | 21 stolen from me +Node 1 (Phys 1): 373 assigned | 370 processed | 21 I stole | 24 stolen from me +Node 2 (Phys 2): 379 assigned | 374 processed | 14 I stole | 19 stolen from me +Node 3 (Phys 3): 351 assigned | 354 processed | 18 I stole | 15 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 82 chunks (5.4%) +Total Cross-Socket Traffic: 79 chunks (5.2%) ================================================================= real 0m0.178s -user 0m1.604s -sys 0m0.847s +user 0m1.700s +sys 0m0.812s -CPU UTILIZATION: 13.769 / 28 +CPU UTILIZATION: 14.112 / 28 ----------------------------------------- @@ -2648,20 +2648,20 @@ CPU UTILIZATION: 13.769 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 379 assigned | 390 processed | 23 I stole | 12 stolen from me -Node 1 (Phys 1): 407 assigned | 401 processed | 17 I stole | 23 stolen from me -Node 2 (Phys 2): 391 assigned | 389 processed | 15 I stole | 17 stolen from me -Node 3 (Phys 3): 350 assigned | 347 processed | 15 I stole | 18 stolen from me +Node 0 (Phys 0): 397 assigned | 401 processed | 26 I stole | 22 stolen from me +Node 1 (Phys 1): 337 assigned | 322 processed | 16 I stole | 31 stolen from me +Node 2 (Phys 2): 392 assigned | 394 processed | 23 I stole | 21 stolen from me +Node 3 (Phys 3): 401 assigned | 410 processed | 24 I stole | 15 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 70 chunks (4.6%) +Total Cross-Socket Traffic: 89 chunks (5.8%) ================================================================= 0 -real 0m0.184s -user 0m1.693s -sys 0m0.878s +real 0m0.173s +user 0m1.686s +sys 0m0.834s -CPU UTILIZATION: 13.972 / 28 +CPU UTILIZATION: 14.566 / 28 ----------------------------------------- @@ -2678,11 +2678,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.722s -user 0m8.663s -sys 0m7.100s +real 0m0.723s +user 0m8.783s +sys 0m7.074s -CPU UTILIZATION: 21.832 / 28 +CPU UTILIZATION: 21.932 / 28 ----------------------------------------- @@ -2700,11 +2700,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.728s -user 0m8.712s -sys 0m7.176s +real 0m0.733s +user 0m8.809s +sys 0m7.226s -CPU UTILIZATION: 21.824 / 28 +CPU UTILIZATION: 21.875 / 28 ----------------------------------------- @@ -2713,19 +2713,19 @@ CPU UTILIZATION: 21.824 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 383 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 383 assigned | 381 processed | 0 I stole | 2 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 2 I stole | 2 stolen from me +Node 1 (Phys 1): 381 assigned | 382 processed | 2 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 1 I stole | 1 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.3%) +Total Cross-Socket Traffic: 5 chunks (0.3%) ================================================================= -real 0m0.723s -user 0m8.604s -sys 0m7.448s +real 0m0.726s +user 0m8.678s +sys 0m7.490s -CPU UTILIZATION: 22.201 / 28 +CPU UTILIZATION: 22.269 / 28 ----------------------------------------- @@ -2734,20 +2734,20 @@ CPU UTILIZATION: 22.201 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 384 processed | 1 I stole | 3 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 378 assigned | 379 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 1 I stole | 2 stolen from me +Node 1 (Phys 1): 383 assigned | 383 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 380 assigned | 379 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 380 assigned | 382 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.3%) +Total Cross-Socket Traffic: 5 chunks (0.3%) ================================================================= 100000000 -real 0m0.717s -user 0m8.822s -sys 0m7.278s +real 0m0.727s +user 0m8.702s +sys 0m7.573s -CPU UTILIZATION: 22.454 / 28 +CPU UTILIZATION: 22.386 / 28 ----------------------------------------- @@ -2764,11 +2764,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.708s -user 0m8.628s -sys 0m6.964s +real 0m0.716s +user 0m8.671s +sys 0m7.022s -CPU UTILIZATION: 22.022 / 28 +CPU UTILIZATION: 21.917 / 28 ----------------------------------------- @@ -2786,11 +2786,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.717s -user 0m8.585s -sys 0m7.124s +real 0m0.719s +user 0m8.729s +sys 0m7.051s -CPU UTILIZATION: 21.909 / 28 +CPU UTILIZATION: 21.947 / 28 ----------------------------------------- @@ -2799,19 +2799,19 @@ CPU UTILIZATION: 21.909 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 385 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 380 assigned | 380 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.2%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m0.708s -user 0m8.566s -sys 0m7.175s +real 0m0.720s +user 0m8.735s +sys 0m7.157s -CPU UTILIZATION: 22.233 / 28 +CPU UTILIZATION: 22.072 / 28 ----------------------------------------- @@ -2820,20 +2820,20 @@ CPU UTILIZATION: 22.233 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 384 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 382 processed | 2 I stole | 1 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 2 I stole | 2 stolen from me Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 5 chunks (0.3%) ================================================================= 100000000 -real 0m0.710s -user 0m8.619s -sys 0m7.278s +real 0m0.718s +user 0m8.777s +sys 0m7.220s -CPU UTILIZATION: 22.390 / 28 +CPU UTILIZATION: 22.279 / 28 ----------------------------------------- @@ -2850,11 +2850,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.197s -user 0m5.882s -sys 0m22.970s +real 0m1.215s +user 0m6.138s +sys 0m22.920s -CPU UTILIZATION: 24.103 / 28 +CPU UTILIZATION: 23.916 / 28 ----------------------------------------- @@ -2863,8 +2863,8 @@ CPU UTILIZATION: 24.103 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -2872,11 +2872,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.203s -user 0m5.950s -sys 0m22.880s +real 0m1.202s +user 0m6.052s +sys 0m23.003s -CPU UTILIZATION: 23.965 / 28 +CPU UTILIZATION: 24.172 / 28 ----------------------------------------- @@ -2885,19 +2885,19 @@ CPU UTILIZATION: 23.965 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3422 assigned | 3392 processed | 148 I stole | 178 stolen from me -Node 1 (Phys 1): 3371 assigned | 3368 processed | 157 I stole | 160 stolen from me -Node 2 (Phys 2): 3406 assigned | 3424 processed | 165 I stole | 147 stolen from me -Node 3 (Phys 3): 3366 assigned | 3381 processed | 164 I stole | 149 stolen from me +Node 0 (Phys 0): 3434 assigned | 3453 processed | 171 I stole | 152 stolen from me +Node 1 (Phys 1): 3345 assigned | 3348 processed | 158 I stole | 155 stolen from me +Node 2 (Phys 2): 3359 assigned | 3318 processed | 153 I stole | 194 stolen from me +Node 3 (Phys 3): 3427 assigned | 3446 processed | 171 I stole | 152 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 634 chunks (4.7%) +Total Cross-Socket Traffic: 653 chunks (4.8%) ================================================================= -real 0m1.346s -user 0m9.111s -sys 0m23.522s +real 0m1.392s +user 0m9.228s +sys 0m23.952s -CPU UTILIZATION: 24.244 / 28 +CPU UTILIZATION: 23.836 / 28 ----------------------------------------- @@ -2906,20 +2906,20 @@ CPU UTILIZATION: 24.244 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3457 assigned | 3444 processed | 167 I stole | 180 stolen from me -Node 1 (Phys 1): 3370 assigned | 3321 processed | 148 I stole | 197 stolen from me -Node 2 (Phys 2): 3360 assigned | 3387 processed | 176 I stole | 149 stolen from me -Node 3 (Phys 3): 3378 assigned | 3413 processed | 170 I stole | 135 stolen from me +Node 0 (Phys 0): 3367 assigned | 3386 processed | 179 I stole | 160 stolen from me +Node 1 (Phys 1): 3406 assigned | 3356 processed | 143 I stole | 193 stolen from me +Node 2 (Phys 2): 3420 assigned | 3427 processed | 172 I stole | 165 stolen from me +Node 3 (Phys 3): 3372 assigned | 3396 processed | 168 I stole | 144 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 661 chunks (4.9%) +Total Cross-Socket Traffic: 662 chunks (4.9%) ================================================================= 0 -real 0m1.347s -user 0m9.061s -sys 0m23.607s +real 0m1.359s +user 0m9.073s +sys 0m23.802s -CPU UTILIZATION: 24.252 / 28 +CPU UTILIZATION: 24.190 / 28 ----------------------------------------- @@ -2928,19 +2928,19 @@ CPU UTILIZATION: 24.252 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.319s -user 0m7.262s -sys 0m24.877s +real 0m1.326s +user 0m7.437s +sys 0m24.854s -CPU UTILIZATION: 24.366 / 28 +CPU UTILIZATION: 24.352 / 28 ----------------------------------------- @@ -2949,20 +2949,20 @@ CPU UTILIZATION: 24.366 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m1.335s -user 0m7.430s -sys 0m25.079s +real 0m1.340s +user 0m7.455s +sys 0m25.319s -CPU UTILIZATION: 24.351 / 28 +CPU UTILIZATION: 24.458 / 28 ----------------------------------------- @@ -2971,19 +2971,19 @@ CPU UTILIZATION: 24.351 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3411 assigned | 3431 processed | 183 I stole | 163 stolen from me -Node 1 (Phys 1): 3386 assigned | 3377 processed | 160 I stole | 169 stolen from me -Node 2 (Phys 2): 3406 assigned | 3374 processed | 149 I stole | 181 stolen from me -Node 3 (Phys 3): 3362 assigned | 3383 processed | 168 I stole | 147 stolen from me +Node 0 (Phys 0): 3345 assigned | 3301 processed | 169 I stole | 213 stolen from me +Node 1 (Phys 1): 3419 assigned | 3434 processed | 191 I stole | 176 stolen from me +Node 2 (Phys 2): 3423 assigned | 3417 processed | 201 I stole | 207 stolen from me +Node 3 (Phys 3): 3378 assigned | 3413 processed | 190 I stole | 155 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 660 chunks (4.9%) +Total Cross-Socket Traffic: 751 chunks (5.5%) ================================================================= -real 0m1.465s -user 0m9.882s -sys 0m26.011s +real 0m1.471s +user 0m10.033s +sys 0m26.118s -CPU UTILIZATION: 24.500 / 28 +CPU UTILIZATION: 24.575 / 28 ----------------------------------------- @@ -2992,20 +2992,20 @@ CPU UTILIZATION: 24.500 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3417 assigned | 3416 processed | 200 I stole | 201 stolen from me -Node 1 (Phys 1): 3396 assigned | 3395 processed | 166 I stole | 167 stolen from me -Node 2 (Phys 2): 3370 assigned | 3373 processed | 179 I stole | 176 stolen from me -Node 3 (Phys 3): 3382 assigned | 3381 processed | 158 I stole | 159 stolen from me +Node 0 (Phys 0): 3381 assigned | 3408 processed | 238 I stole | 211 stolen from me +Node 1 (Phys 1): 3393 assigned | 3386 processed | 201 I stole | 208 stolen from me +Node 2 (Phys 2): 3366 assigned | 3356 processed | 195 I stole | 205 stolen from me +Node 3 (Phys 3): 3425 assigned | 3415 processed | 191 I stole | 201 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 703 chunks (5.2%) +Total Cross-Socket Traffic: 825 chunks (6.1%) ================================================================= -28349 -real 0m1.481s -user 0m9.880s -sys 0m26.520s +28350 +real 0m1.480s +user 0m10.020s +sys 0m26.564s -CPU UTILIZATION: 24.577 / 28 +CPU UTILIZATION: 24.718 / 28 ----------------------------------------- @@ -3022,11 +3022,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m2.073s -user 0m27.474s -sys 0m24.970s +real 0m2.082s +user 0m27.716s +sys 0m24.903s -CPU UTILIZATION: 25.298 / 28 +CPU UTILIZATION: 25.273 / 28 ----------------------------------------- @@ -3044,11 +3044,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m2.093s -user 0m27.535s -sys 0m25.330s +real 0m2.100s +user 0m27.617s +sys 0m25.289s -CPU UTILIZATION: 25.258 / 28 +CPU UTILIZATION: 25.193 / 28 ----------------------------------------- @@ -3057,19 +3057,19 @@ CPU UTILIZATION: 25.258 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3405 assigned | 3391 processed | 165 I stole | 179 stolen from me -Node 1 (Phys 1): 3394 assigned | 3384 processed | 154 I stole | 164 stolen from me -Node 2 (Phys 2): 3378 assigned | 3391 processed | 156 I stole | 143 stolen from me -Node 3 (Phys 3): 3388 assigned | 3399 processed | 147 I stole | 136 stolen from me +Node 0 (Phys 0): 3410 assigned | 3388 processed | 123 I stole | 145 stolen from me +Node 1 (Phys 1): 3390 assigned | 3403 processed | 148 I stole | 135 stolen from me +Node 2 (Phys 2): 3379 assigned | 3382 processed | 103 I stole | 100 stolen from me +Node 3 (Phys 3): 3386 assigned | 3392 processed | 109 I stole | 103 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 622 chunks (4.6%) +Total Cross-Socket Traffic: 483 chunks (3.6%) ================================================================= -real 0m2.194s -user 0m29.623s -sys 0m26.115s +real 0m2.196s +user 0m29.550s +sys 0m26.369s -CPU UTILIZATION: 25.404 / 28 +CPU UTILIZATION: 25.464 / 28 ----------------------------------------- @@ -3078,20 +3078,20 @@ CPU UTILIZATION: 25.404 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3412 assigned | 3393 processed | 131 I stole | 150 stolen from me -Node 1 (Phys 1): 3412 assigned | 3394 processed | 125 I stole | 143 stolen from me -Node 2 (Phys 2): 3369 assigned | 3391 processed | 136 I stole | 114 stolen from me -Node 3 (Phys 3): 3372 assigned | 3387 processed | 132 I stole | 117 stolen from me +Node 0 (Phys 0): 3462 assigned | 3409 processed | 167 I stole | 220 stolen from me +Node 1 (Phys 1): 3396 assigned | 3385 processed | 180 I stole | 191 stolen from me +Node 2 (Phys 2): 3350 assigned | 3388 processed | 210 I stole | 172 stolen from me +Node 3 (Phys 3): 3357 assigned | 3383 processed | 197 I stole | 171 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 524 chunks (3.9%) +Total Cross-Socket Traffic: 754 chunks (5.6%) ================================================================= 100000000 -real 0m2.204s -user 0m29.678s -sys 0m26.432s +real 0m2.212s +user 0m29.774s +sys 0m26.786s -CPU UTILIZATION: 25.458 / 28 +CPU UTILIZATION: 25.569 / 28 ----------------------------------------- @@ -3100,19 +3100,19 @@ CPU UTILIZATION: 25.458 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.738s -user 0m1.903s -sys 0m15.654s +real 0m0.737s +user 0m1.906s +sys 0m15.669s -CPU UTILIZATION: 23.789 / 28 +CPU UTILIZATION: 23.846 / 28 ----------------------------------------- @@ -3122,19 +3122,19 @@ CPU UTILIZATION: 23.789 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.740s -user 0m1.944s -sys 0m15.608s +real 0m0.737s +user 0m1.932s +sys 0m15.670s -CPU UTILIZATION: 23.718 / 28 +CPU UTILIZATION: 23.883 / 28 ----------------------------------------- @@ -3143,19 +3143,19 @@ CPU UTILIZATION: 23.718 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3431 assigned | 3409 processed | 189 I stole | 211 stolen from me -Node 1 (Phys 1): 3428 assigned | 3421 processed | 195 I stole | 202 stolen from me -Node 2 (Phys 2): 3403 assigned | 3411 processed | 197 I stole | 189 stolen from me -Node 3 (Phys 3): 3303 assigned | 3324 processed | 196 I stole | 175 stolen from me +Node 0 (Phys 0): 3453 assigned | 3393 processed | 224 I stole | 284 stolen from me +Node 1 (Phys 1): 3371 assigned | 3371 processed | 259 I stole | 259 stolen from me +Node 2 (Phys 2): 3332 assigned | 3356 processed | 239 I stole | 215 stolen from me +Node 3 (Phys 3): 3409 assigned | 3445 processed | 240 I stole | 204 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 777 chunks (5.7%) +Total Cross-Socket Traffic: 962 chunks (7.1%) ================================================================= -real 0m1.093s -user 0m4.743s -sys 0m20.332s +real 0m1.080s +user 0m4.834s +sys 0m20.387s -CPU UTILIZATION: 22.941 / 28 +CPU UTILIZATION: 23.352 / 28 ----------------------------------------- @@ -3164,20 +3164,20 @@ CPU UTILIZATION: 22.941 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3423 assigned | 3426 processed | 267 I stole | 264 stolen from me -Node 1 (Phys 1): 3376 assigned | 3329 processed | 248 I stole | 295 stolen from me -Node 2 (Phys 2): 3386 assigned | 3420 processed | 269 I stole | 235 stolen from me -Node 3 (Phys 3): 3380 assigned | 3390 processed | 247 I stole | 237 stolen from me +Node 0 (Phys 0): 3440 assigned | 3453 processed | 219 I stole | 206 stolen from me +Node 1 (Phys 1): 3371 assigned | 3344 processed | 204 I stole | 231 stolen from me +Node 2 (Phys 2): 3408 assigned | 3413 processed | 202 I stole | 197 stolen from me +Node 3 (Phys 3): 3346 assigned | 3355 processed | 191 I stole | 182 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1031 chunks (7.6%) +Total Cross-Socket Traffic: 816 chunks (6.0%) ================================================================= 0 -real 0m1.072s -user 0m4.733s -sys 0m20.325s +real 0m1.084s +user 0m4.863s +sys 0m20.357s -CPU UTILIZATION: 23.375 / 28 +CPU UTILIZATION: 23.265 / 28 ----------------------------------------- @@ -3186,19 +3186,19 @@ CPU UTILIZATION: 23.375 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.832s -user 0m3.437s -sys 0m16.548s +user 0m3.460s +sys 0m16.563s -CPU UTILIZATION: 24.020 / 28 +CPU UTILIZATION: 24.066 / 28 ----------------------------------------- @@ -3207,20 +3207,20 @@ CPU UTILIZATION: 24.020 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m0.835s -user 0m3.442s -sys 0m16.946s +real 0m0.838s +user 0m3.490s +sys 0m16.998s -CPU UTILIZATION: 24.416 / 28 +CPU UTILIZATION: 24.448 / 28 ----------------------------------------- @@ -3229,19 +3229,19 @@ CPU UTILIZATION: 24.416 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3404 assigned | 3363 processed | 228 I stole | 269 stolen from me -Node 1 (Phys 1): 3380 assigned | 3391 processed | 246 I stole | 235 stolen from me -Node 2 (Phys 2): 3407 assigned | 3430 processed | 251 I stole | 228 stolen from me -Node 3 (Phys 3): 3374 assigned | 3381 processed | 219 I stole | 212 stolen from me +Node 0 (Phys 0): 3304 assigned | 3256 processed | 237 I stole | 285 stolen from me +Node 1 (Phys 1): 3456 assigned | 3459 processed | 246 I stole | 243 stolen from me +Node 2 (Phys 2): 3356 assigned | 3358 processed | 234 I stole | 232 stolen from me +Node 3 (Phys 3): 3449 assigned | 3492 processed | 237 I stole | 194 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 944 chunks (7.0%) +Total Cross-Socket Traffic: 954 chunks (7.0%) ================================================================= real 0m1.182s -user 0m6.235s -sys 0m21.673s +user 0m6.171s +sys 0m21.873s -CPU UTILIZATION: 23.610 / 28 +CPU UTILIZATION: 23.725 / 28 ----------------------------------------- @@ -3250,20 +3250,20 @@ CPU UTILIZATION: 23.610 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3405 assigned | 3346 processed | 199 I stole | 258 stolen from me -Node 1 (Phys 1): 3460 assigned | 3481 processed | 243 I stole | 222 stolen from me -Node 2 (Phys 2): 3395 assigned | 3382 processed | 224 I stole | 237 stolen from me -Node 3 (Phys 3): 3305 assigned | 3356 processed | 235 I stole | 184 stolen from me +Node 0 (Phys 0): 3465 assigned | 3432 processed | 197 I stole | 230 stolen from me +Node 1 (Phys 1): 3439 assigned | 3472 processed | 235 I stole | 202 stolen from me +Node 2 (Phys 2): 3318 assigned | 3328 processed | 209 I stole | 199 stolen from me +Node 3 (Phys 3): 3343 assigned | 3333 processed | 203 I stole | 213 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 901 chunks (6.6%) +Total Cross-Socket Traffic: 844 chunks (6.2%) ================================================================= -14837 -real 0m1.205s -user 0m6.286s -sys 0m22.116s +14836 +real 0m1.204s +user 0m6.294s +sys 0m22.231s -CPU UTILIZATION: 23.570 / 28 +CPU UTILIZATION: 23.691 / 28 ----------------------------------------- @@ -3274,17 +3274,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.601s -user 0m24.297s -sys 0m16.749s +real 0m1.604s +user 0m24.190s +sys 0m16.850s -CPU UTILIZATION: 25.637 / 28 +CPU UTILIZATION: 25.586 / 28 ----------------------------------------- @@ -3294,19 +3294,19 @@ CPU UTILIZATION: 25.637 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.612s -user 0m24.217s -sys 0m17.175s +real 0m1.611s +user 0m24.244s +sys 0m17.169s -CPU UTILIZATION: 25.677 / 28 +CPU UTILIZATION: 25.706 / 28 ----------------------------------------- @@ -3315,19 +3315,19 @@ CPU UTILIZATION: 25.677 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3394 assigned | 3397 processed | 320 I stole | 317 stolen from me -Node 1 (Phys 1): 3415 assigned | 3403 processed | 291 I stole | 303 stolen from me -Node 2 (Phys 2): 3409 assigned | 3394 processed | 278 I stole | 293 stolen from me -Node 3 (Phys 3): 3347 assigned | 3371 processed | 302 I stole | 278 stolen from me +Node 0 (Phys 0): 3470 assigned | 3411 processed | 365 I stole | 424 stolen from me +Node 1 (Phys 1): 3417 assigned | 3437 processed | 380 I stole | 360 stolen from me +Node 2 (Phys 2): 3315 assigned | 3343 processed | 359 I stole | 331 stolen from me +Node 3 (Phys 3): 3363 assigned | 3374 processed | 334 I stole | 323 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1191 chunks (8.8%) +Total Cross-Socket Traffic: 1438 chunks (10.6%) ================================================================= -real 0m1.889s -user 0m27.205s -sys 0m20.958s +real 0m1.930s +user 0m27.364s +sys 0m21.197s -CPU UTILIZATION: 25.496 / 28 +CPU UTILIZATION: 25.161 / 28 ----------------------------------------- @@ -3336,20 +3336,20 @@ CPU UTILIZATION: 25.496 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3422 assigned | 3418 processed | 231 I stole | 235 stolen from me -Node 1 (Phys 1): 3378 assigned | 3385 processed | 234 I stole | 227 stolen from me -Node 2 (Phys 2): 3408 assigned | 3376 processed | 185 I stole | 217 stolen from me -Node 3 (Phys 3): 3357 assigned | 3386 processed | 215 I stole | 186 stolen from me +Node 0 (Phys 0): 3429 assigned | 3373 processed | 338 I stole | 394 stolen from me +Node 1 (Phys 1): 3404 assigned | 3428 processed | 376 I stole | 352 stolen from me +Node 2 (Phys 2): 3353 assigned | 3384 processed | 381 I stole | 350 stolen from me +Node 3 (Phys 3): 3379 assigned | 3380 processed | 352 I stole | 351 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 865 chunks (6.4%) +Total Cross-Socket Traffic: 1447 chunks (10.7%) ================================================================= 100000000 -real 0m1.901s -user 0m27.249s -sys 0m21.326s +real 0m1.919s +user 0m27.434s +sys 0m21.548s -CPU UTILIZATION: 25.552 / 28 +CPU UTILIZATION: 25.524 / 28 ----------------------------------------- @@ -3358,19 +3358,19 @@ CPU UTILIZATION: 25.552 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.202s -user 0m5.978s -sys 0m22.975s +real 0m1.212s +user 0m6.238s +sys 0m22.817s -CPU UTILIZATION: 24.087 / 28 +CPU UTILIZATION: 23.972 / 28 ----------------------------------------- @@ -3379,20 +3379,20 @@ CPU UTILIZATION: 24.087 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.203s -user 0m5.975s -sys 0m22.919s +real 0m1.208s +user 0m6.002s +sys 0m23.107s -CPU UTILIZATION: 24.018 / 28 +CPU UTILIZATION: 24.096 / 28 ----------------------------------------- @@ -3401,19 +3401,19 @@ CPU UTILIZATION: 24.018 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3421 assigned | 3414 processed | 179 I stole | 186 stolen from me -Node 1 (Phys 1): 3376 assigned | 3361 processed | 176 I stole | 191 stolen from me -Node 2 (Phys 2): 3307 assigned | 3324 processed | 176 I stole | 159 stolen from me -Node 3 (Phys 3): 3461 assigned | 3466 processed | 184 I stole | 179 stolen from me +Node 0 (Phys 0): 3346 assigned | 3300 processed | 142 I stole | 188 stolen from me +Node 1 (Phys 1): 3426 assigned | 3452 processed | 161 I stole | 135 stolen from me +Node 2 (Phys 2): 3393 assigned | 3409 processed | 144 I stole | 128 stolen from me +Node 3 (Phys 3): 3400 assigned | 3404 processed | 143 I stole | 139 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 715 chunks (5.3%) +Total Cross-Socket Traffic: 590 chunks (4.3%) ================================================================= -real 0m1.346s -user 0m8.933s -sys 0m23.648s +real 0m1.354s +user 0m9.083s +sys 0m23.813s -CPU UTILIZATION: 24.205 / 28 +CPU UTILIZATION: 24.295 / 28 ----------------------------------------- @@ -3422,20 +3422,20 @@ CPU UTILIZATION: 24.205 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3413 assigned | 3403 processed | 162 I stole | 172 stolen from me -Node 1 (Phys 1): 3383 assigned | 3391 processed | 176 I stole | 168 stolen from me -Node 2 (Phys 2): 3385 assigned | 3373 processed | 168 I stole | 180 stolen from me -Node 3 (Phys 3): 3384 assigned | 3398 processed | 164 I stole | 150 stolen from me +Node 0 (Phys 0): 3429 assigned | 3424 processed | 160 I stole | 165 stolen from me +Node 1 (Phys 1): 3423 assigned | 3429 processed | 165 I stole | 159 stolen from me +Node 2 (Phys 2): 3398 assigned | 3414 processed | 172 I stole | 156 stolen from me +Node 3 (Phys 3): 3315 assigned | 3298 processed | 143 I stole | 160 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 670 chunks (4.9%) +Total Cross-Socket Traffic: 640 chunks (4.7%) ================================================================= 0 -real 0m1.350s -user 0m9.067s -sys 0m23.645s +real 0m1.358s +user 0m9.172s +sys 0m23.801s -CPU UTILIZATION: 24.231 / 28 +CPU UTILIZATION: 24.280 / 28 ----------------------------------------- @@ -3452,11 +3452,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.317s -user 0m7.165s -sys 0m24.928s +real 0m1.326s +user 0m7.453s +sys 0m24.892s -CPU UTILIZATION: 24.368 / 28 +CPU UTILIZATION: 24.392 / 28 ----------------------------------------- @@ -3466,19 +3466,19 @@ CPU UTILIZATION: 24.368 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m1.330s -user 0m7.366s -sys 0m25.202s +real 0m1.339s +user 0m7.451s +sys 0m25.299s -CPU UTILIZATION: 24.487 / 28 +CPU UTILIZATION: 24.458 / 28 ----------------------------------------- @@ -3487,19 +3487,19 @@ CPU UTILIZATION: 24.487 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3414 assigned | 3438 processed | 191 I stole | 167 stolen from me -Node 1 (Phys 1): 3418 assigned | 3391 processed | 180 I stole | 207 stolen from me -Node 2 (Phys 2): 3393 assigned | 3401 processed | 174 I stole | 166 stolen from me -Node 3 (Phys 3): 3340 assigned | 3335 processed | 167 I stole | 172 stolen from me +Node 0 (Phys 0): 3387 assigned | 3384 processed | 183 I stole | 186 stolen from me +Node 1 (Phys 1): 3400 assigned | 3375 processed | 160 I stole | 185 stolen from me +Node 2 (Phys 2): 3407 assigned | 3391 processed | 155 I stole | 171 stolen from me +Node 3 (Phys 3): 3371 assigned | 3415 processed | 196 I stole | 152 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 712 chunks (5.2%) +Total Cross-Socket Traffic: 694 chunks (5.1%) ================================================================= -real 0m1.476s -user 0m9.773s -sys 0m26.179s +real 0m1.475s +user 0m9.880s +sys 0m26.359s -CPU UTILIZATION: 24.357 / 28 +CPU UTILIZATION: 24.568 / 28 ----------------------------------------- @@ -3508,20 +3508,20 @@ CPU UTILIZATION: 24.357 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3413 assigned | 3390 processed | 192 I stole | 215 stolen from me -Node 1 (Phys 1): 3392 assigned | 3429 processed | 203 I stole | 166 stolen from me -Node 2 (Phys 2): 3378 assigned | 3345 processed | 164 I stole | 197 stolen from me -Node 3 (Phys 3): 3382 assigned | 3401 processed | 184 I stole | 165 stolen from me +Node 0 (Phys 0): 3417 assigned | 3425 processed | 188 I stole | 180 stolen from me +Node 1 (Phys 1): 3478 assigned | 3486 processed | 189 I stole | 181 stolen from me +Node 2 (Phys 2): 3419 assigned | 3410 processed | 169 I stole | 178 stolen from me +Node 3 (Phys 3): 3251 assigned | 3244 processed | 183 I stole | 190 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 743 chunks (5.5%) +Total Cross-Socket Traffic: 729 chunks (5.4%) ================================================================= -28349 -real 0m1.475s -user 0m9.762s -sys 0m26.590s +28350 +real 0m1.555s +user 0m10.150s +sys 0m26.824s -CPU UTILIZATION: 24.645 / 28 +CPU UTILIZATION: 23.777 / 28 ----------------------------------------- @@ -3530,19 +3530,19 @@ CPU UTILIZATION: 24.645 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m2.065s -user 0m27.591s -sys 0m24.634s +real 0m2.089s +user 0m27.713s +sys 0m24.854s -CPU UTILIZATION: 25.290 / 28 +CPU UTILIZATION: 25.163 / 28 ----------------------------------------- @@ -3551,20 +3551,20 @@ CPU UTILIZATION: 25.290 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m2.091s -user 0m27.508s -sys 0m25.351s +real 0m2.090s +user 0m27.604s +sys 0m25.415s -CPU UTILIZATION: 25.279 / 28 +CPU UTILIZATION: 25.367 / 28 ----------------------------------------- @@ -3573,19 +3573,19 @@ CPU UTILIZATION: 25.279 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3406 assigned | 3398 processed | 174 I stole | 182 stolen from me -Node 1 (Phys 1): 3381 assigned | 3379 processed | 166 I stole | 168 stolen from me -Node 2 (Phys 2): 3411 assigned | 3402 processed | 152 I stole | 161 stolen from me -Node 3 (Phys 3): 3367 assigned | 3386 processed | 149 I stole | 130 stolen from me +Node 0 (Phys 0): 3433 assigned | 3406 processed | 175 I stole | 202 stolen from me +Node 1 (Phys 1): 3398 assigned | 3403 processed | 192 I stole | 187 stolen from me +Node 2 (Phys 2): 3375 assigned | 3378 processed | 172 I stole | 169 stolen from me +Node 3 (Phys 3): 3359 assigned | 3378 processed | 181 I stole | 162 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 641 chunks (4.7%) +Total Cross-Socket Traffic: 720 chunks (5.3%) ================================================================= -real 0m2.191s -user 0m29.455s -sys 0m26.227s +real 0m2.199s +user 0m29.627s +sys 0m26.367s -CPU UTILIZATION: 25.413 / 28 +CPU UTILIZATION: 25.463 / 28 ----------------------------------------- @@ -3594,20 +3594,20 @@ CPU UTILIZATION: 25.413 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3421 assigned | 3382 processed | 150 I stole | 189 stolen from me -Node 1 (Phys 1): 3380 assigned | 3384 processed | 179 I stole | 175 stolen from me -Node 2 (Phys 2): 3369 assigned | 3386 processed | 175 I stole | 158 stolen from me -Node 3 (Phys 3): 3395 assigned | 3413 processed | 162 I stole | 144 stolen from me +Node 0 (Phys 0): 3416 assigned | 3396 processed | 168 I stole | 188 stolen from me +Node 1 (Phys 1): 3389 assigned | 3397 processed | 164 I stole | 156 stolen from me +Node 2 (Phys 2): 3388 assigned | 3395 processed | 167 I stole | 160 stolen from me +Node 3 (Phys 3): 3372 assigned | 3377 processed | 150 I stole | 145 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 666 chunks (4.9%) +Total Cross-Socket Traffic: 649 chunks (4.8%) ================================================================= 100000000 -real 0m2.206s -user 0m29.438s -sys 0m26.747s +real 0m2.214s +user 0m29.841s +sys 0m26.643s -CPU UTILIZATION: 25.469 / 28 +CPU UTILIZATION: 25.512 / 28 ----------------------------------------- @@ -3616,19 +3616,19 @@ CPU UTILIZATION: 25.469 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 104 assigned | 104 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.737s -user 0m1.914s -sys 0m15.615s +user 0m1.884s +sys 0m15.709s -CPU UTILIZATION: 23.784 / 28 +CPU UTILIZATION: 23.871 / 28 ----------------------------------------- @@ -3638,19 +3638,19 @@ CPU UTILIZATION: 23.784 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.741s -user 0m1.859s -sys 0m15.722s +real 0m0.738s +user 0m1.972s +sys 0m15.669s -CPU UTILIZATION: 23.726 / 28 +CPU UTILIZATION: 23.903 / 28 ----------------------------------------- @@ -3659,19 +3659,19 @@ CPU UTILIZATION: 23.726 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3382 assigned | 3370 processed | 251 I stole | 263 stolen from me -Node 1 (Phys 1): 3397 assigned | 3372 processed | 227 I stole | 252 stolen from me -Node 2 (Phys 2): 3374 assigned | 3407 processed | 256 I stole | 223 stolen from me -Node 3 (Phys 3): 3412 assigned | 3416 processed | 220 I stole | 216 stolen from me +Node 0 (Phys 0): 3423 assigned | 3389 processed | 206 I stole | 240 stolen from me +Node 1 (Phys 1): 3355 assigned | 3389 processed | 232 I stole | 198 stolen from me +Node 2 (Phys 2): 3367 assigned | 3351 processed | 195 I stole | 211 stolen from me +Node 3 (Phys 3): 3420 assigned | 3436 processed | 215 I stole | 199 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 954 chunks (7.0%) +Total Cross-Socket Traffic: 848 chunks (6.3%) ================================================================= -real 0m1.070s -user 0m4.830s -sys 0m20.225s +real 0m1.083s +user 0m4.822s +sys 0m20.389s -CPU UTILIZATION: 23.415 / 28 +CPU UTILIZATION: 23.278 / 28 ----------------------------------------- @@ -3680,20 +3680,20 @@ CPU UTILIZATION: 23.415 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3433 assigned | 3367 processed | 205 I stole | 271 stolen from me -Node 1 (Phys 1): 3389 assigned | 3460 processed | 283 I stole | 212 stolen from me -Node 2 (Phys 2): 3358 assigned | 3333 processed | 211 I stole | 236 stolen from me -Node 3 (Phys 3): 3385 assigned | 3405 processed | 222 I stole | 202 stolen from me +Node 0 (Phys 0): 3409 assigned | 3407 processed | 251 I stole | 253 stolen from me +Node 1 (Phys 1): 3394 assigned | 3384 processed | 237 I stole | 247 stolen from me +Node 2 (Phys 2): 3380 assigned | 3404 processed | 266 I stole | 242 stolen from me +Node 3 (Phys 3): 3382 assigned | 3370 processed | 217 I stole | 229 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 921 chunks (6.8%) +Total Cross-Socket Traffic: 971 chunks (7.2%) ================================================================= 0 -real 0m1.074s -user 0m4.782s -sys 0m20.304s +real 0m1.071s +user 0m4.918s +sys 0m20.261s -CPU UTILIZATION: 23.357 / 28 +CPU UTILIZATION: 23.509 / 28 ----------------------------------------- @@ -3710,11 +3710,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.831s -user 0m3.446s -sys 0m16.549s +real 0m0.835s +user 0m3.478s +sys 0m16.594s -CPU UTILIZATION: 24.061 / 28 +CPU UTILIZATION: 24.038 / 28 ----------------------------------------- @@ -3724,19 +3724,19 @@ CPU UTILIZATION: 24.061 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m0.840s -user 0m3.462s -sys 0m16.937s +real 0m0.839s +user 0m3.561s +sys 0m16.893s -CPU UTILIZATION: 24.284 / 28 +CPU UTILIZATION: 24.379 / 28 ----------------------------------------- @@ -3745,19 +3745,19 @@ CPU UTILIZATION: 24.284 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3375 assigned | 3355 processed | 210 I stole | 230 stolen from me -Node 1 (Phys 1): 3373 assigned | 3358 processed | 218 I stole | 233 stolen from me -Node 2 (Phys 2): 3421 assigned | 3467 processed | 240 I stole | 194 stolen from me -Node 3 (Phys 3): 3396 assigned | 3385 processed | 208 I stole | 219 stolen from me +Node 0 (Phys 0): 3362 assigned | 3288 processed | 218 I stole | 292 stolen from me +Node 1 (Phys 1): 3430 assigned | 3449 processed | 246 I stole | 227 stolen from me +Node 2 (Phys 2): 3421 assigned | 3500 processed | 282 I stole | 203 stolen from me +Node 3 (Phys 3): 3352 assigned | 3328 processed | 215 I stole | 239 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 876 chunks (6.5%) +Total Cross-Socket Traffic: 961 chunks (7.1%) ================================================================= real 0m1.184s -user 0m6.039s -sys 0m21.830s +user 0m6.275s +sys 0m21.859s -CPU UTILIZATION: 23.538 / 28 +CPU UTILIZATION: 23.761 / 28 ----------------------------------------- @@ -3766,20 +3766,20 @@ CPU UTILIZATION: 23.538 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3348 assigned | 3337 processed | 238 I stole | 249 stolen from me -Node 1 (Phys 1): 3445 assigned | 3461 processed | 244 I stole | 228 stolen from me -Node 2 (Phys 2): 3409 assigned | 3383 processed | 197 I stole | 223 stolen from me -Node 3 (Phys 3): 3363 assigned | 3384 processed | 221 I stole | 200 stolen from me +Node 0 (Phys 0): 3502 assigned | 3468 processed | 280 I stole | 314 stolen from me +Node 1 (Phys 1): 3353 assigned | 3338 processed | 247 I stole | 262 stolen from me +Node 2 (Phys 2): 3414 assigned | 3442 processed | 282 I stole | 254 stolen from me +Node 3 (Phys 3): 3296 assigned | 3317 processed | 244 I stole | 223 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 900 chunks (6.6%) +Total Cross-Socket Traffic: 1053 chunks (7.8%) ================================================================= -14837 -real 0m1.211s -user 0m6.284s -sys 0m22.218s +14836 +real 0m1.199s +user 0m6.291s +sys 0m22.230s -CPU UTILIZATION: 23.535 / 28 +CPU UTILIZATION: 23.787 / 28 ----------------------------------------- @@ -3788,19 +3788,19 @@ CPU UTILIZATION: 23.535 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.597s -user 0m24.283s -sys 0m16.726s +real 0m1.600s +user 0m24.174s +sys 0m16.932s -CPU UTILIZATION: 25.678 / 28 +CPU UTILIZATION: 25.691 / 28 ----------------------------------------- @@ -3811,8 +3811,8 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= @@ -3820,9 +3820,9 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) 100000000 real 0m1.613s user 0m24.257s -sys 0m17.149s +sys 0m17.185s -CPU UTILIZATION: 25.670 / 28 +CPU UTILIZATION: 25.692 / 28 ----------------------------------------- @@ -3831,19 +3831,19 @@ CPU UTILIZATION: 25.670 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3426 assigned | 3373 processed | 328 I stole | 381 stolen from me -Node 1 (Phys 1): 3419 assigned | 3413 processed | 333 I stole | 339 stolen from me -Node 2 (Phys 2): 3355 assigned | 3401 processed | 341 I stole | 295 stolen from me -Node 3 (Phys 3): 3365 assigned | 3378 processed | 333 I stole | 320 stolen from me +Node 0 (Phys 0): 3393 assigned | 3390 processed | 350 I stole | 353 stolen from me +Node 1 (Phys 1): 3419 assigned | 3422 processed | 332 I stole | 329 stolen from me +Node 2 (Phys 2): 3434 assigned | 3408 processed | 342 I stole | 368 stolen from me +Node 3 (Phys 3): 3319 assigned | 3345 processed | 329 I stole | 303 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1335 chunks (9.8%) +Total Cross-Socket Traffic: 1353 chunks (10.0%) ================================================================= -real 0m1.888s -user 0m27.120s -sys 0m20.913s +real 0m1.900s +user 0m27.353s +sys 0m21.068s -CPU UTILIZATION: 25.441 / 28 +CPU UTILIZATION: 25.484 / 28 ----------------------------------------- @@ -3852,20 +3852,20 @@ CPU UTILIZATION: 25.441 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3360 assigned | 3371 processed | 346 I stole | 335 stolen from me -Node 1 (Phys 1): 3386 assigned | 3430 processed | 330 I stole | 286 stolen from me -Node 2 (Phys 2): 3423 assigned | 3380 processed | 295 I stole | 338 stolen from me -Node 3 (Phys 3): 3396 assigned | 3384 processed | 285 I stole | 297 stolen from me +Node 0 (Phys 0): 3453 assigned | 3406 processed | 344 I stole | 391 stolen from me +Node 1 (Phys 1): 3357 assigned | 3375 processed | 362 I stole | 344 stolen from me +Node 2 (Phys 2): 3379 assigned | 3440 processed | 368 I stole | 307 stolen from me +Node 3 (Phys 3): 3376 assigned | 3344 processed | 291 I stole | 323 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1256 chunks (9.3%) +Total Cross-Socket Traffic: 1365 chunks (10.1%) ================================================================= 100000000 -real 0m1.908s -user 0m27.327s -sys 0m21.358s +real 0m1.911s +user 0m27.410s +sys 0m21.510s -CPU UTILIZATION: 25.516 / 28 +CPU UTILIZATION: 25.599 / 28 ----------------------------------------- @@ -3882,11 +3882,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.173s -user 0m5.589s -sys 0m22.596s +real 0m1.175s +user 0m5.719s +sys 0m22.635s -CPU UTILIZATION: 24.028 / 28 +CPU UTILIZATION: 24.131 / 28 ----------------------------------------- @@ -3895,20 +3895,20 @@ CPU UTILIZATION: 24.028 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.175s -user 0m5.548s -sys 0m22.596s +real 0m1.177s +user 0m5.735s +sys 0m22.616s -CPU UTILIZATION: 23.952 / 28 +CPU UTILIZATION: 24.087 / 28 ----------------------------------------- @@ -3917,19 +3917,19 @@ CPU UTILIZATION: 23.952 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3412 assigned | 3446 processed | 189 I stole | 155 stolen from me -Node 1 (Phys 1): 3436 assigned | 3423 processed | 141 I stole | 154 stolen from me -Node 2 (Phys 2): 3358 assigned | 3357 processed | 154 I stole | 155 stolen from me -Node 3 (Phys 3): 3359 assigned | 3339 processed | 148 I stole | 168 stolen from me +Node 0 (Phys 0): 3429 assigned | 3399 processed | 183 I stole | 213 stolen from me +Node 1 (Phys 1): 3404 assigned | 3406 processed | 178 I stole | 176 stolen from me +Node 2 (Phys 2): 3405 assigned | 3424 processed | 186 I stole | 167 stolen from me +Node 3 (Phys 3): 3327 assigned | 3336 processed | 166 I stole | 157 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 632 chunks (4.7%) +Total Cross-Socket Traffic: 713 chunks (5.3%) ================================================================= -real 0m1.323s -user 0m8.520s -sys 0m23.353s +real 0m1.324s +user 0m8.624s +sys 0m23.480s -CPU UTILIZATION: 24.091 / 28 +CPU UTILIZATION: 24.247 / 28 ----------------------------------------- @@ -3938,20 +3938,20 @@ CPU UTILIZATION: 24.091 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3441 assigned | 3430 processed | 151 I stole | 162 stolen from me -Node 1 (Phys 1): 3410 assigned | 3422 processed | 169 I stole | 157 stolen from me -Node 2 (Phys 2): 3355 assigned | 3336 processed | 167 I stole | 186 stolen from me -Node 3 (Phys 3): 3359 assigned | 3377 processed | 174 I stole | 156 stolen from me +Node 0 (Phys 0): 3322 assigned | 3266 processed | 134 I stole | 190 stolen from me +Node 1 (Phys 1): 3432 assigned | 3480 processed | 181 I stole | 133 stolen from me +Node 2 (Phys 2): 3401 assigned | 3383 processed | 134 I stole | 152 stolen from me +Node 3 (Phys 3): 3410 assigned | 3436 processed | 168 I stole | 142 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 661 chunks (4.9%) +Total Cross-Socket Traffic: 617 chunks (4.5%) ================================================================= 0 -real 0m1.322s -user 0m8.786s -sys 0m22.995s +real 0m1.329s +user 0m8.753s +sys 0m23.433s -CPU UTILIZATION: 24.040 / 28 +CPU UTILIZATION: 24.218 / 28 ----------------------------------------- @@ -3962,17 +3962,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.268s -user 0m6.667s -sys 0m23.986s +real 0m1.270s +user 0m6.953s +sys 0m23.891s -CPU UTILIZATION: 24.174 / 28 +CPU UTILIZATION: 24.286 / 28 ----------------------------------------- @@ -3981,8 +3981,8 @@ CPU UTILIZATION: 24.174 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -3990,11 +3990,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m1.369s -user 0m7.411s -sys 0m23.915s +real 0m1.376s +user 0m7.530s +sys 0m24.045s -CPU UTILIZATION: 22.882 / 28 +CPU UTILIZATION: 22.946 / 28 ----------------------------------------- @@ -4003,19 +4003,19 @@ CPU UTILIZATION: 22.882 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3399 assigned | 3378 processed | 176 I stole | 197 stolen from me -Node 1 (Phys 1): 3389 assigned | 3363 processed | 176 I stole | 202 stolen from me -Node 2 (Phys 2): 3403 assigned | 3427 processed | 180 I stole | 156 stolen from me -Node 3 (Phys 3): 3374 assigned | 3397 processed | 192 I stole | 169 stolen from me +Node 0 (Phys 0): 3341 assigned | 3355 processed | 202 I stole | 188 stolen from me +Node 1 (Phys 1): 3379 assigned | 3315 processed | 160 I stole | 224 stolen from me +Node 2 (Phys 2): 3421 assigned | 3445 processed | 206 I stole | 182 stolen from me +Node 3 (Phys 3): 3424 assigned | 3450 processed | 202 I stole | 176 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 724 chunks (5.3%) +Total Cross-Socket Traffic: 770 chunks (5.7%) ================================================================= real 0m1.412s -user 0m9.376s -sys 0m24.978s +user 0m9.587s +sys 0m24.973s -CPU UTILIZATION: 24.330 / 28 +CPU UTILIZATION: 24.475 / 28 ----------------------------------------- @@ -4024,20 +4024,20 @@ CPU UTILIZATION: 24.330 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3419 assigned | 3400 processed | 86 I stole | 105 stolen from me -Node 1 (Phys 1): 3413 assigned | 3408 processed | 90 I stole | 95 stolen from me -Node 2 (Phys 2): 3380 assigned | 3389 processed | 88 I stole | 79 stolen from me -Node 3 (Phys 3): 3353 assigned | 3368 processed | 91 I stole | 76 stolen from me +Node 0 (Phys 0): 3408 assigned | 3393 processed | 84 I stole | 99 stolen from me +Node 1 (Phys 1): 3413 assigned | 3401 processed | 82 I stole | 94 stolen from me +Node 2 (Phys 2): 3378 assigned | 3397 processed | 90 I stole | 71 stolen from me +Node 3 (Phys 3): 3366 assigned | 3374 processed | 85 I stole | 77 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 355 chunks (2.6%) +Total Cross-Socket Traffic: 341 chunks (2.5%) ================================================================= -28349 -real 0m1.478s -user 0m9.358s -sys 0m25.062s +28350 +real 0m1.489s +user 0m9.535s +sys 0m25.180s -CPU UTILIZATION: 23.288 / 28 +CPU UTILIZATION: 23.314 / 28 ----------------------------------------- @@ -4046,19 +4046,19 @@ CPU UTILIZATION: 23.288 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m2.014s -user 0m26.998s -sys 0m23.819s +real 0m2.019s +user 0m27.300s +sys 0m23.679s -CPU UTILIZATION: 25.231 / 28 +CPU UTILIZATION: 25.249 / 28 ----------------------------------------- @@ -4068,19 +4068,19 @@ CPU UTILIZATION: 25.231 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m2.232s -user 0m25.016s -sys 0m25.500s +real 0m2.243s +user 0m24.989s +sys 0m25.765s -CPU UTILIZATION: 22.632 / 28 +CPU UTILIZATION: 22.627 / 28 ----------------------------------------- @@ -4089,19 +4089,19 @@ CPU UTILIZATION: 22.632 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3433 assigned | 3408 processed | 171 I stole | 196 stolen from me -Node 1 (Phys 1): 3379 assigned | 3371 processed | 156 I stole | 164 stolen from me -Node 2 (Phys 2): 3379 assigned | 3388 processed | 166 I stole | 157 stolen from me -Node 3 (Phys 3): 3374 assigned | 3398 processed | 167 I stole | 143 stolen from me +Node 0 (Phys 0): 3396 assigned | 3391 processed | 198 I stole | 203 stolen from me +Node 1 (Phys 1): 3394 assigned | 3386 processed | 201 I stole | 209 stolen from me +Node 2 (Phys 2): 3393 assigned | 3411 processed | 199 I stole | 181 stolen from me +Node 3 (Phys 3): 3382 assigned | 3377 processed | 185 I stole | 190 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 660 chunks (4.9%) +Total Cross-Socket Traffic: 783 chunks (5.8%) ================================================================= -real 0m2.132s -user 0m28.947s -sys 0m24.985s +real 0m2.142s +user 0m29.193s +sys 0m25.101s -CPU UTILIZATION: 25.296 / 28 +CPU UTILIZATION: 25.347 / 28 ----------------------------------------- @@ -4110,20 +4110,20 @@ CPU UTILIZATION: 25.296 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3395 assigned | 3399 processed | 18 I stole | 14 stolen from me -Node 1 (Phys 1): 3388 assigned | 3382 processed | 11 I stole | 17 stolen from me -Node 2 (Phys 2): 3388 assigned | 3392 processed | 17 I stole | 13 stolen from me -Node 3 (Phys 3): 3394 assigned | 3392 processed | 13 I stole | 15 stolen from me +Node 0 (Phys 0): 3386 assigned | 3385 processed | 31 I stole | 32 stolen from me +Node 1 (Phys 1): 3419 assigned | 3414 processed | 29 I stole | 34 stolen from me +Node 2 (Phys 2): 3380 assigned | 3381 processed | 25 I stole | 24 stolen from me +Node 3 (Phys 3): 3380 assigned | 3385 processed | 25 I stole | 20 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 59 chunks (0.4%) +Total Cross-Socket Traffic: 110 chunks (0.8%) ================================================================= 100000000 real 0m2.334s -user 0m26.956s -sys 0m26.688s +user 0m26.601s +sys 0m27.228s -CPU UTILIZATION: 22.983 / 28 +CPU UTILIZATION: 23.062 / 28 ----------------------------------------- @@ -4132,19 +4132,19 @@ CPU UTILIZATION: 22.983 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 104 assigned | 104 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.735s -user 0m1.818s -sys 0m15.548s +user 0m1.831s +sys 0m15.659s -CPU UTILIZATION: 23.627 / 28 +CPU UTILIZATION: 23.795 / 28 ----------------------------------------- @@ -4154,19 +4154,19 @@ CPU UTILIZATION: 23.627 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.738s -user 0m1.821s -sys 0m15.603s +real 0m0.732s +user 0m1.860s +sys 0m15.644s -CPU UTILIZATION: 23.609 / 28 +CPU UTILIZATION: 23.912 / 28 ----------------------------------------- @@ -4175,19 +4175,19 @@ CPU UTILIZATION: 23.609 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3406 assigned | 3385 processed | 255 I stole | 276 stolen from me -Node 1 (Phys 1): 3320 assigned | 3299 processed | 255 I stole | 276 stolen from me -Node 2 (Phys 2): 3396 assigned | 3415 processed | 269 I stole | 250 stolen from me -Node 3 (Phys 3): 3443 assigned | 3466 processed | 243 I stole | 220 stolen from me +Node 0 (Phys 0): 3415 assigned | 3379 processed | 194 I stole | 230 stolen from me +Node 1 (Phys 1): 3416 assigned | 3392 processed | 179 I stole | 203 stolen from me +Node 2 (Phys 2): 3374 assigned | 3428 processed | 231 I stole | 177 stolen from me +Node 3 (Phys 3): 3360 assigned | 3366 processed | 199 I stole | 193 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1022 chunks (7.5%) +Total Cross-Socket Traffic: 803 chunks (5.9%) ================================================================= -real 0m1.053s -user 0m4.513s -sys 0m20.118s +real 0m1.071s +user 0m4.637s +sys 0m20.103s -CPU UTILIZATION: 23.391 / 28 +CPU UTILIZATION: 23.099 / 28 ----------------------------------------- @@ -4196,20 +4196,20 @@ CPU UTILIZATION: 23.391 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3406 assigned | 3378 processed | 218 I stole | 246 stolen from me -Node 1 (Phys 1): 3420 assigned | 3399 processed | 223 I stole | 244 stolen from me -Node 2 (Phys 2): 3372 assigned | 3368 processed | 208 I stole | 212 stolen from me -Node 3 (Phys 3): 3367 assigned | 3420 processed | 229 I stole | 176 stolen from me +Node 0 (Phys 0): 3452 assigned | 3416 processed | 261 I stole | 297 stolen from me +Node 1 (Phys 1): 3426 assigned | 3457 processed | 290 I stole | 259 stolen from me +Node 2 (Phys 2): 3319 assigned | 3331 processed | 260 I stole | 248 stolen from me +Node 3 (Phys 3): 3368 assigned | 3361 processed | 243 I stole | 250 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 878 chunks (6.5%) +Total Cross-Socket Traffic: 1054 chunks (7.8%) ================================================================= 0 -real 0m1.058s -user 0m4.558s -sys 0m20.127s +real 0m1.063s +user 0m4.656s +sys 0m20.085s -CPU UTILIZATION: 23.331 / 28 +CPU UTILIZATION: 23.274 / 28 ----------------------------------------- @@ -4218,19 +4218,19 @@ CPU UTILIZATION: 23.331 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 107 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 107 assigned | 108 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.2%) ================================================================= -real 0m0.797s -user 0m3.335s -sys 0m15.855s +real 0m0.814s +user 0m3.365s +sys 0m15.845s -CPU UTILIZATION: 24.077 / 28 +CPU UTILIZATION: 23.599 / 28 ----------------------------------------- @@ -4248,11 +4248,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m0.878s -user 0m3.319s -sys 0m16.852s +real 0m0.896s +user 0m3.285s +sys 0m17.200s -CPU UTILIZATION: 22.973 / 28 +CPU UTILIZATION: 22.862 / 28 ----------------------------------------- @@ -4261,19 +4261,19 @@ CPU UTILIZATION: 22.973 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3430 assigned | 3386 processed | 218 I stole | 262 stolen from me -Node 1 (Phys 1): 3444 assigned | 3491 processed | 251 I stole | 204 stolen from me -Node 2 (Phys 2): 3386 assigned | 3377 processed | 211 I stole | 220 stolen from me -Node 3 (Phys 3): 3305 assigned | 3311 processed | 219 I stole | 213 stolen from me +Node 0 (Phys 0): 3444 assigned | 3435 processed | 220 I stole | 229 stolen from me +Node 1 (Phys 1): 3408 assigned | 3439 processed | 224 I stole | 193 stolen from me +Node 2 (Phys 2): 3330 assigned | 3283 processed | 185 I stole | 232 stolen from me +Node 3 (Phys 3): 3383 assigned | 3408 processed | 201 I stole | 176 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 899 chunks (6.6%) +Total Cross-Socket Traffic: 830 chunks (6.1%) ================================================================= -real 0m1.141s -user 0m5.740s +real 0m1.172s +user 0m5.861s sys 0m20.924s -CPU UTILIZATION: 23.368 / 28 +CPU UTILIZATION: 22.854 / 28 ----------------------------------------- @@ -4282,20 +4282,20 @@ CPU UTILIZATION: 23.368 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3419 assigned | 3407 processed | 176 I stole | 188 stolen from me -Node 1 (Phys 1): 3410 assigned | 3401 processed | 170 I stole | 179 stolen from me -Node 2 (Phys 2): 3375 assigned | 3384 processed | 186 I stole | 177 stolen from me -Node 3 (Phys 3): 3361 assigned | 3373 processed | 157 I stole | 145 stolen from me +Node 0 (Phys 0): 3385 assigned | 3374 processed | 192 I stole | 203 stolen from me +Node 1 (Phys 1): 3402 assigned | 3397 processed | 183 I stole | 188 stolen from me +Node 2 (Phys 2): 3378 assigned | 3352 processed | 169 I stole | 195 stolen from me +Node 3 (Phys 3): 3400 assigned | 3442 processed | 185 I stole | 143 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 689 chunks (5.1%) +Total Cross-Socket Traffic: 729 chunks (5.4%) ================================================================= -14832 -real 0m1.197s -user 0m5.566s -sys 0m21.809s +14837 +real 0m1.196s +user 0m5.798s +sys 0m21.765s -CPU UTILIZATION: 22.869 / 28 +CPU UTILIZATION: 23.045 / 28 ----------------------------------------- @@ -4305,18 +4305,18 @@ CPU UTILIZATION: 22.869 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.572s -user 0m24.154s -sys 0m16.090s +real 0m1.568s +user 0m24.159s +sys 0m16.182s -CPU UTILIZATION: 25.600 / 28 +CPU UTILIZATION: 25.727 / 28 ----------------------------------------- @@ -4325,20 +4325,20 @@ CPU UTILIZATION: 25.600 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.688s -user 0m22.384s -sys 0m16.176s +real 0m1.673s +user 0m22.341s +sys 0m16.014s -CPU UTILIZATION: 22.843 / 28 +CPU UTILIZATION: 22.925 / 28 ----------------------------------------- @@ -4347,19 +4347,19 @@ CPU UTILIZATION: 22.843 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3440 assigned | 3405 processed | 209 I stole | 244 stolen from me -Node 1 (Phys 1): 3370 assigned | 3381 processed | 197 I stole | 186 stolen from me -Node 2 (Phys 2): 3358 assigned | 3384 processed | 229 I stole | 203 stolen from me -Node 3 (Phys 3): 3397 assigned | 3395 processed | 172 I stole | 174 stolen from me +Node 0 (Phys 0): 3388 assigned | 3395 processed | 402 I stole | 395 stolen from me +Node 1 (Phys 1): 3367 assigned | 3365 processed | 371 I stole | 373 stolen from me +Node 2 (Phys 2): 3417 assigned | 3400 processed | 355 I stole | 372 stolen from me +Node 3 (Phys 3): 3393 assigned | 3405 processed | 355 I stole | 343 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 807 chunks (5.9%) +Total Cross-Socket Traffic: 1483 chunks (10.9%) ================================================================= -real 0m1.837s -user 0m26.635s -sys 0m20.120s +real 0m1.859s +user 0m26.875s +sys 0m20.277s -CPU UTILIZATION: 25.451 / 28 +CPU UTILIZATION: 25.364 / 28 ----------------------------------------- @@ -4368,20 +4368,20 @@ CPU UTILIZATION: 25.451 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3430 assigned | 3397 processed | 101 I stole | 134 stolen from me -Node 1 (Phys 1): 3398 assigned | 3394 processed | 113 I stole | 117 stolen from me -Node 2 (Phys 2): 3371 assigned | 3386 processed | 106 I stole | 91 stolen from me -Node 3 (Phys 3): 3366 assigned | 3388 processed | 100 I stole | 78 stolen from me +Node 0 (Phys 0): 3410 assigned | 3393 processed | 112 I stole | 129 stolen from me +Node 1 (Phys 1): 3394 assigned | 3399 processed | 100 I stole | 95 stolen from me +Node 2 (Phys 2): 3398 assigned | 3382 processed | 76 I stole | 92 stolen from me +Node 3 (Phys 3): 3363 assigned | 3391 processed | 100 I stole | 72 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 420 chunks (3.1%) +Total Cross-Socket Traffic: 388 chunks (2.9%) ================================================================= 100000000 -real 0m2.056s -user 0m24.551s -sys 0m21.774s +real 0m2.044s +user 0m24.412s +sys 0m21.543s -CPU UTILIZATION: 22.531 / 28 +CPU UTILIZATION: 22.482 / 28 ----------------------------------------- @@ -4390,19 +4390,19 @@ CPU UTILIZATION: 22.531 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 103 assigned | 103 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m4.300s -user 1m55.289s -sys 0m1.770s +real 0m4.326s +user 1m55.733s +sys 0m1.864s -CPU UTILIZATION: 27.223 / 28 +CPU UTILIZATION: 27.183 / 28 ----------------------------------------- @@ -4411,20 +4411,20 @@ CPU UTILIZATION: 27.223 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m4.280s -user 1m54.794s -sys 0m1.785s +real 0m4.305s +user 1m55.013s +sys 0m1.810s -CPU UTILIZATION: 27.238 / 28 +CPU UTILIZATION: 27.136 / 28 ----------------------------------------- @@ -4433,19 +4433,19 @@ CPU UTILIZATION: 27.238 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3308 assigned | 3309 processed | 7 I stole | 6 stolen from me -Node 1 (Phys 1): 3426 assigned | 3424 processed | 3 I stole | 5 stolen from me -Node 2 (Phys 2): 3471 assigned | 3467 processed | 2 I stole | 6 stolen from me -Node 3 (Phys 3): 3360 assigned | 3365 processed | 7 I stole | 2 stolen from me +Node 0 (Phys 0): 3347 assigned | 3345 processed | 8 I stole | 10 stolen from me +Node 1 (Phys 1): 3466 assigned | 3473 processed | 10 I stole | 3 stolen from me +Node 2 (Phys 2): 3219 assigned | 3220 processed | 9 I stole | 8 stolen from me +Node 3 (Phys 3): 3533 assigned | 3527 processed | 6 I stole | 12 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 19 chunks (0.1%) +Total Cross-Socket Traffic: 33 chunks (0.2%) ================================================================= -real 0m4.389s -user 1m57.353s -sys 0m2.397s +real 0m4.407s +user 1m57.634s +sys 0m2.406s -CPU UTILIZATION: 27.284 / 28 +CPU UTILIZATION: 27.238 / 28 ----------------------------------------- @@ -4454,20 +4454,20 @@ CPU UTILIZATION: 27.284 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3383 assigned | 3387 processed | 9 I stole | 5 stolen from me -Node 1 (Phys 1): 3504 assigned | 3506 processed | 11 I stole | 9 stolen from me -Node 2 (Phys 2): 3468 assigned | 3461 processed | 4 I stole | 11 stolen from me -Node 3 (Phys 3): 3210 assigned | 3211 processed | 10 I stole | 9 stolen from me +Node 0 (Phys 0): 3399 assigned | 3401 processed | 3 I stole | 1 stolen from me +Node 1 (Phys 1): 3331 assigned | 3331 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 3409 assigned | 3408 processed | 1 I stole | 2 stolen from me +Node 3 (Phys 3): 3426 assigned | 3425 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 34 chunks (0.3%) +Total Cross-Socket Traffic: 5 chunks (0.0%) ================================================================= 0 -real 0m4.380s -user 1m57.022s -sys 0m2.388s +real 0m4.407s +user 1m57.600s +sys 0m2.489s -CPU UTILIZATION: 27.262 / 28 +CPU UTILIZATION: 27.249 / 28 ----------------------------------------- @@ -4476,19 +4476,19 @@ CPU UTILIZATION: 27.262 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m4.726s -user 2m6.202s -sys 0m2.562s +real 0m4.756s +user 2m6.539s +sys 0m2.690s -CPU UTILIZATION: 27.245 / 28 +CPU UTILIZATION: 27.171 / 28 ----------------------------------------- @@ -4497,20 +4497,20 @@ CPU UTILIZATION: 27.245 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m4.729s -user 2m5.532s -sys 0m2.823s +real 0m4.753s +user 2m6.503s +sys 0m2.878s -CPU UTILIZATION: 27.142 / 28 +CPU UTILIZATION: 27.220 / 28 ----------------------------------------- @@ -4519,19 +4519,19 @@ CPU UTILIZATION: 27.142 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3480 assigned | 3480 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 3358 assigned | 3357 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 3309 assigned | 3307 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 3418 assigned | 3421 processed | 3 I stole | 0 stolen from me +Node 0 (Phys 0): 3513 assigned | 3511 processed | 15 I stole | 17 stolen from me +Node 1 (Phys 1): 3304 assigned | 3305 processed | 18 I stole | 17 stolen from me +Node 2 (Phys 2): 3364 assigned | 3365 processed | 19 I stole | 18 stolen from me +Node 3 (Phys 3): 3384 assigned | 3384 processed | 22 I stole | 22 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.0%) +Total Cross-Socket Traffic: 74 chunks (0.5%) ================================================================= -real 0m4.825s -user 2m8.482s -sys 0m3.233s +real 0m4.861s +user 2m9.148s +sys 0m3.213s -CPU UTILIZATION: 27.298 / 28 +CPU UTILIZATION: 27.229 / 28 ----------------------------------------- @@ -4540,20 +4540,20 @@ CPU UTILIZATION: 27.298 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3364 assigned | 3364 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 3437 assigned | 3437 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 3465 assigned | 3465 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3299 assigned | 3299 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 3488 assigned | 3489 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 3346 assigned | 3346 processed | 3 I stole | 3 stolen from me +Node 2 (Phys 2): 3432 assigned | 3430 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 3299 assigned | 3300 processed | 2 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 7 chunks (0.1%) ================================================================= -28349 -real 0m4.825s -user 2m8.309s -sys 0m3.566s +28350 +real 0m4.886s +user 2m9.973s +sys 0m3.446s -CPU UTILIZATION: 27.331 / 28 +CPU UTILIZATION: 27.306 / 28 ----------------------------------------- @@ -4562,19 +4562,19 @@ CPU UTILIZATION: 27.331 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 104 assigned | 104 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m8.050s -user 2m49.468s -sys 0m51.388s +real 0m8.182s +user 2m51.962s +sys 0m52.611s -CPU UTILIZATION: 27.435 / 28 +CPU UTILIZATION: 27.447 / 28 ----------------------------------------- @@ -4584,19 +4584,19 @@ CPU UTILIZATION: 27.435 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 104 assigned | 104 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 103 assigned | 103 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m8.085s -user 2m48.917s -sys 0m52.477s +real 0m8.142s +user 2m50.715s +sys 0m52.535s -CPU UTILIZATION: 27.383 / 28 +CPU UTILIZATION: 27.419 / 28 ----------------------------------------- @@ -4605,19 +4605,19 @@ CPU UTILIZATION: 27.383 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3433 assigned | 3433 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 3342 assigned | 3342 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 3467 assigned | 3467 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3323 assigned | 3323 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 3419 assigned | 3420 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 3510 assigned | 3510 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 3385 assigned | 3385 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 3251 assigned | 3250 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.0%) ================================================================= -real 0m8.160s -user 2m52.033s -sys 0m51.868s +real 0m8.255s +user 2m53.671s +sys 0m53.221s -CPU UTILIZATION: 27.438 / 28 +CPU UTILIZATION: 27.485 / 28 ----------------------------------------- @@ -4626,20 +4626,20 @@ CPU UTILIZATION: 27.438 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3388 assigned | 3389 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 3461 assigned | 3460 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 3404 assigned | 3405 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 3312 assigned | 3311 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 3459 assigned | 3459 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 3384 assigned | 3384 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 3409 assigned | 3409 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 3313 assigned | 3313 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (0.0%) ================================================================= 100000000 -real 0m8.160s -user 2m51.897s -sys 0m52.569s +real 0m8.346s +user 2m55.996s +sys 0m53.632s -CPU UTILIZATION: 27.508 / 28 +CPU UTILIZATION: 27.513 / 28 ----------------------------------------- @@ -4648,19 +4648,19 @@ CPU UTILIZATION: 27.508 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 109 assigned | 109 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m4.682s -user 2m5.225s -sys 0m1.606s +real 0m4.653s +user 2m4.006s +sys 0m1.676s -CPU UTILIZATION: 27.089 / 28 +CPU UTILIZATION: 27.010 / 28 ----------------------------------------- @@ -4670,19 +4670,19 @@ CPU UTILIZATION: 27.089 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 109 assigned | 109 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 103 assigned | 103 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m4.629s -user 2m3.789s -sys 0m1.699s +real 0m4.650s +user 2m3.864s +sys 0m1.582s -CPU UTILIZATION: 27.109 / 28 +CPU UTILIZATION: 26.977 / 28 ----------------------------------------- @@ -4691,19 +4691,19 @@ CPU UTILIZATION: 27.109 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3391 assigned | 3387 processed | 85 I stole | 89 stolen from me -Node 1 (Phys 1): 3404 assigned | 3395 processed | 71 I stole | 80 stolen from me -Node 2 (Phys 2): 3404 assigned | 3408 processed | 84 I stole | 80 stolen from me -Node 3 (Phys 3): 3366 assigned | 3375 processed | 69 I stole | 60 stolen from me +Node 0 (Phys 0): 3350 assigned | 3366 processed | 57 I stole | 41 stolen from me +Node 1 (Phys 1): 3448 assigned | 3446 processed | 44 I stole | 46 stolen from me +Node 2 (Phys 2): 3413 assigned | 3406 processed | 42 I stole | 49 stolen from me +Node 3 (Phys 3): 3354 assigned | 3347 processed | 48 I stole | 55 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 309 chunks (2.3%) +Total Cross-Socket Traffic: 191 chunks (1.4%) ================================================================= -real 0m4.402s -user 1m56.395s -sys 0m2.942s +real 0m4.401s +user 1m57.168s +sys 0m2.288s -CPU UTILIZATION: 27.109 / 28 +CPU UTILIZATION: 27.142 / 28 ----------------------------------------- @@ -4712,20 +4712,20 @@ CPU UTILIZATION: 27.109 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3421 assigned | 3451 processed | 83 I stole | 53 stolen from me -Node 1 (Phys 1): 3319 assigned | 3310 processed | 53 I stole | 62 stolen from me -Node 2 (Phys 2): 3411 assigned | 3415 processed | 63 I stole | 59 stolen from me -Node 3 (Phys 3): 3414 assigned | 3389 processed | 53 I stole | 78 stolen from me +Node 0 (Phys 0): 3378 assigned | 3358 processed | 38 I stole | 58 stolen from me +Node 1 (Phys 1): 3367 assigned | 3376 processed | 46 I stole | 37 stolen from me +Node 2 (Phys 2): 3427 assigned | 3429 processed | 47 I stole | 45 stolen from me +Node 3 (Phys 3): 3393 assigned | 3402 processed | 46 I stole | 37 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 252 chunks (1.9%) +Total Cross-Socket Traffic: 177 chunks (1.3%) ================================================================= 0 -real 0m4.413s -user 1m56.703s -sys 0m2.841s +real 0m4.398s +user 1m57.160s +sys 0m2.249s -CPU UTILIZATION: 27.089 / 28 +CPU UTILIZATION: 27.150 / 28 ----------------------------------------- @@ -4734,19 +4734,19 @@ CPU UTILIZATION: 27.089 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 104 assigned | 104 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m5.016s -user 2m13.704s -sys 0m2.408s +real 0m5.029s +user 2m14.177s +sys 0m2.380s -CPU UTILIZATION: 27.135 / 28 +CPU UTILIZATION: 27.153 / 28 ----------------------------------------- @@ -4755,20 +4755,20 @@ CPU UTILIZATION: 27.135 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m5.044s -user 2m14.068s -sys 0m2.732s +real 0m5.050s +user 2m14.143s +sys 0m2.690s -CPU UTILIZATION: 27.121 / 28 +CPU UTILIZATION: 27.095 / 28 ----------------------------------------- @@ -4777,19 +4777,19 @@ CPU UTILIZATION: 27.121 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3390 assigned | 3375 processed | 27 I stole | 42 stolen from me -Node 1 (Phys 1): 3435 assigned | 3418 processed | 26 I stole | 43 stolen from me -Node 2 (Phys 2): 3413 assigned | 3430 processed | 45 I stole | 28 stolen from me -Node 3 (Phys 3): 3327 assigned | 3342 processed | 44 I stole | 29 stolen from me +Node 0 (Phys 0): 3422 assigned | 3402 processed | 60 I stole | 80 stolen from me +Node 1 (Phys 1): 3415 assigned | 3419 processed | 76 I stole | 72 stolen from me +Node 2 (Phys 2): 3425 assigned | 3436 processed | 75 I stole | 64 stolen from me +Node 3 (Phys 3): 3303 assigned | 3308 processed | 68 I stole | 63 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 142 chunks (1.0%) +Total Cross-Socket Traffic: 279 chunks (2.1%) ================================================================= -real 0m4.907s -user 2m9.535s -sys 0m3.705s +real 0m4.827s +user 2m8.085s +sys 0m2.982s -CPU UTILIZATION: 27.153 / 28 +CPU UTILIZATION: 27.152 / 28 ----------------------------------------- @@ -4798,20 +4798,20 @@ CPU UTILIZATION: 27.153 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3420 assigned | 3440 processed | 68 I stole | 48 stolen from me -Node 1 (Phys 1): 3402 assigned | 3394 processed | 48 I stole | 56 stolen from me -Node 2 (Phys 2): 3413 assigned | 3385 processed | 38 I stole | 66 stolen from me -Node 3 (Phys 3): 3330 assigned | 3346 processed | 62 I stole | 46 stolen from me +Node 0 (Phys 0): 3439 assigned | 3425 processed | 33 I stole | 47 stolen from me +Node 1 (Phys 1): 3401 assigned | 3411 processed | 42 I stole | 32 stolen from me +Node 2 (Phys 2): 3385 assigned | 3397 processed | 36 I stole | 24 stolen from me +Node 3 (Phys 3): 3340 assigned | 3332 processed | 26 I stole | 34 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 216 chunks (1.6%) +Total Cross-Socket Traffic: 137 chunks (1.0%) ================================================================= 14836 -real 0m4.852s -user 2m8.158s -sys 0m3.968s +real 0m4.851s +user 2m8.473s +sys 0m3.389s -CPU UTILIZATION: 27.231 / 28 +CPU UTILIZATION: 27.182 / 28 ----------------------------------------- @@ -4820,19 +4820,19 @@ CPU UTILIZATION: 27.231 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m8.318s -user 2m56.139s -sys 0m50.922s +real 0m8.317s +user 2m55.085s +sys 0m51.983s -CPU UTILIZATION: 27.297 / 28 +CPU UTILIZATION: 27.301 / 28 ----------------------------------------- @@ -4842,19 +4842,19 @@ CPU UTILIZATION: 27.297 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m8.286s -user 2m54.882s -sys 0m50.980s +real 0m8.375s +user 2m55.294s +sys 0m52.182s -CPU UTILIZATION: 27.258 / 28 +CPU UTILIZATION: 27.161 / 28 ----------------------------------------- @@ -4863,19 +4863,19 @@ CPU UTILIZATION: 27.258 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3369 assigned | 3354 processed | 31 I stole | 46 stolen from me -Node 1 (Phys 1): 3429 assigned | 3416 processed | 24 I stole | 37 stolen from me -Node 2 (Phys 2): 3396 assigned | 3411 processed | 40 I stole | 25 stolen from me -Node 3 (Phys 3): 3371 assigned | 3384 processed | 34 I stole | 21 stolen from me +Node 0 (Phys 0): 3420 assigned | 3420 processed | 31 I stole | 31 stolen from me +Node 1 (Phys 1): 3326 assigned | 3337 processed | 24 I stole | 13 stolen from me +Node 2 (Phys 2): 3422 assigned | 3413 processed | 20 I stole | 29 stolen from me +Node 3 (Phys 3): 3397 assigned | 3395 processed | 20 I stole | 22 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 129 chunks (1.0%) +Total Cross-Socket Traffic: 95 chunks (0.7%) ================================================================= -real 0m8.154s -user 2m51.563s -sys 0m52.427s +real 0m8.173s +user 2m52.016s +sys 0m52.445s -CPU UTILIZATION: 27.469 / 28 +CPU UTILIZATION: 27.463 / 28 ----------------------------------------- @@ -4884,20 +4884,20 @@ CPU UTILIZATION: 27.469 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3394 assigned | 3386 processed | 27 I stole | 35 stolen from me -Node 1 (Phys 1): 3372 assigned | 3392 processed | 47 I stole | 27 stolen from me -Node 2 (Phys 2): 3343 assigned | 3347 processed | 32 I stole | 28 stolen from me -Node 3 (Phys 3): 3456 assigned | 3440 processed | 19 I stole | 35 stolen from me +Node 0 (Phys 0): 3397 assigned | 3391 processed | 34 I stole | 40 stolen from me +Node 1 (Phys 1): 3449 assigned | 3439 processed | 31 I stole | 41 stolen from me +Node 2 (Phys 2): 3362 assigned | 3380 processed | 37 I stole | 19 stolen from me +Node 3 (Phys 3): 3357 assigned | 3355 processed | 25 I stole | 27 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 125 chunks (0.9%) +Total Cross-Socket Traffic: 127 chunks (0.9%) ================================================================= 100000000 -real 0m8.160s -user 2m50.987s -sys 0m53.356s +real 0m8.210s +user 2m52.063s +sys 0m53.382s -CPU UTILIZATION: 27.493 / 28 +CPU UTILIZATION: 27.459 / 28 ----------------------------------------- @@ -4906,19 +4906,19 @@ CPU UTILIZATION: 27.493 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.433s -user 0m1.301s -sys 0m1.407s +real 0m0.398s +user 0m1.397s +sys 0m1.447s -CPU UTILIZATION: 6.254 / 28 +CPU UTILIZATION: 7.145 / 28 ----------------------------------------- @@ -4928,19 +4928,19 @@ CPU UTILIZATION: 6.254 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.2%) ================================================================= 0 -real 0m0.417s -user 0m1.344s -sys 0m1.407s +real 0m0.427s +user 0m1.318s +sys 0m1.501s -CPU UTILIZATION: 6.597 / 28 +CPU UTILIZATION: 6.601 / 28 ----------------------------------------- @@ -4949,19 +4949,19 @@ CPU UTILIZATION: 6.597 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3414 assigned | 3421 processed | 7 I stole | 0 stolen from me -Node 1 (Phys 1): 3393 assigned | 3398 processed | 8 I stole | 3 stolen from me -Node 2 (Phys 2): 3383 assigned | 3377 processed | 0 I stole | 6 stolen from me -Node 3 (Phys 3): 3375 assigned | 3369 processed | 0 I stole | 6 stolen from me +Node 0 (Phys 0): 3397 assigned | 3406 processed | 9 I stole | 0 stolen from me +Node 1 (Phys 1): 3399 assigned | 3400 processed | 3 I stole | 2 stolen from me +Node 2 (Phys 2): 3396 assigned | 3394 processed | 3 I stole | 5 stolen from me +Node 3 (Phys 3): 3373 assigned | 3365 processed | 0 I stole | 8 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 15 chunks (0.1%) ================================================================= -real 0m0.566s -user 0m4.020s -sys 0m3.659s +real 0m0.552s +user 0m4.003s +sys 0m3.590s -CPU UTILIZATION: 13.567 / 28 +CPU UTILIZATION: 13.755 / 28 ----------------------------------------- @@ -4970,20 +4970,20 @@ CPU UTILIZATION: 13.567 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3397 assigned | 3403 processed | 6 I stole | 0 stolen from me -Node 1 (Phys 1): 3410 assigned | 3404 processed | 2 I stole | 8 stolen from me -Node 2 (Phys 2): 3402 assigned | 3406 processed | 5 I stole | 1 stolen from me -Node 3 (Phys 3): 3356 assigned | 3352 processed | 2 I stole | 6 stolen from me +Node 0 (Phys 0): 3385 assigned | 3387 processed | 5 I stole | 3 stolen from me +Node 1 (Phys 1): 3412 assigned | 3422 processed | 10 I stole | 0 stolen from me +Node 2 (Phys 2): 3412 assigned | 3407 processed | 2 I stole | 7 stolen from me +Node 3 (Phys 3): 3356 assigned | 3349 processed | 0 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 15 chunks (0.1%) +Total Cross-Socket Traffic: 17 chunks (0.1%) ================================================================= 0 -real 0m0.557s -user 0m3.975s -sys 0m3.590s +real 0m0.547s +user 0m3.960s +sys 0m3.569s -CPU UTILIZATION: 13.581 / 28 +CPU UTILIZATION: 13.764 / 28 ----------------------------------------- @@ -5000,11 +5000,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.821s -user 0m9.217s -sys 0m9.492s +real 0m0.827s +user 0m9.379s +sys 0m9.606s -CPU UTILIZATION: 22.788 / 28 +CPU UTILIZATION: 22.956 / 28 ----------------------------------------- @@ -5022,11 +5022,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.899s -user 0m9.251s -sys 0m9.920s +real 0m0.906s +user 0m9.357s +sys 0m10.021s -CPU UTILIZATION: 21.324 / 28 +CPU UTILIZATION: 21.388 / 28 ----------------------------------------- @@ -5035,19 +5035,19 @@ CPU UTILIZATION: 21.324 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3389 assigned | 3369 processed | 109 I stole | 129 stolen from me -Node 1 (Phys 1): 3419 assigned | 3421 processed | 126 I stole | 124 stolen from me -Node 2 (Phys 2): 3451 assigned | 3461 processed | 124 I stole | 114 stolen from me -Node 3 (Phys 3): 3306 assigned | 3314 processed | 122 I stole | 114 stolen from me +Node 0 (Phys 0): 3376 assigned | 3367 processed | 120 I stole | 129 stolen from me +Node 1 (Phys 1): 3420 assigned | 3412 processed | 98 I stole | 106 stolen from me +Node 2 (Phys 2): 3375 assigned | 3395 processed | 125 I stole | 105 stolen from me +Node 3 (Phys 3): 3394 assigned | 3391 processed | 102 I stole | 105 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 481 chunks (3.5%) +Total Cross-Socket Traffic: 445 chunks (3.3%) ================================================================= -real 0m0.987s -user 0m11.912s -sys 0m10.951s +real 0m1.020s +user 0m12.161s +sys 0m11.062s -CPU UTILIZATION: 23.164 / 28 +CPU UTILIZATION: 22.767 / 28 ----------------------------------------- @@ -5056,20 +5056,20 @@ CPU UTILIZATION: 23.164 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3484 assigned | 3485 processed | 132 I stole | 131 stolen from me -Node 1 (Phys 1): 3412 assigned | 3378 processed | 93 I stole | 127 stolen from me -Node 2 (Phys 2): 3386 assigned | 3392 processed | 110 I stole | 104 stolen from me -Node 3 (Phys 3): 3283 assigned | 3310 processed | 123 I stole | 96 stolen from me +Node 0 (Phys 0): 3418 assigned | 3390 processed | 95 I stole | 123 stolen from me +Node 1 (Phys 1): 3399 assigned | 3392 processed | 105 I stole | 112 stolen from me +Node 2 (Phys 2): 3411 assigned | 3424 processed | 123 I stole | 110 stolen from me +Node 3 (Phys 3): 3337 assigned | 3359 processed | 118 I stole | 96 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 458 chunks (3.4%) +Total Cross-Socket Traffic: 441 chunks (3.3%) ================================================================= 100000000 -real 0m1.012s -user 0m12.080s -sys 0m11.354s +real 0m1.028s +user 0m12.346s +sys 0m11.368s -CPU UTILIZATION: 23.156 / 28 +CPU UTILIZATION: 23.068 / 28 ----------------------------------------- @@ -5086,11 +5086,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.798s -user 0m9.209s -sys 0m9.080s +real 0m0.812s +user 0m9.400s +sys 0m9.133s -CPU UTILIZATION: 22.918 / 28 +CPU UTILIZATION: 22.823 / 28 ----------------------------------------- @@ -5100,19 +5100,19 @@ CPU UTILIZATION: 22.918 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.885s -user 0m9.352s -sys 0m9.306s +real 0m0.894s +user 0m9.451s +sys 0m9.472s -CPU UTILIZATION: 21.082 / 28 +CPU UTILIZATION: 21.166 / 28 ----------------------------------------- @@ -5121,19 +5121,19 @@ CPU UTILIZATION: 21.082 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3347 assigned | 3358 processed | 126 I stole | 115 stolen from me -Node 1 (Phys 1): 3450 assigned | 3447 processed | 101 I stole | 104 stolen from me -Node 2 (Phys 2): 3320 assigned | 3305 processed | 99 I stole | 114 stolen from me -Node 3 (Phys 3): 3448 assigned | 3455 processed | 105 I stole | 98 stolen from me +Node 0 (Phys 0): 3489 assigned | 3524 processed | 105 I stole | 70 stolen from me +Node 1 (Phys 1): 3293 assigned | 3249 processed | 58 I stole | 102 stolen from me +Node 2 (Phys 2): 3370 assigned | 3369 processed | 81 I stole | 82 stolen from me +Node 3 (Phys 3): 3413 assigned | 3423 processed | 80 I stole | 70 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 431 chunks (3.2%) +Total Cross-Socket Traffic: 324 chunks (2.4%) ================================================================= -real 0m0.980s -user 0m11.849s -sys 0m10.578s +real 0m1.005s +user 0m12.175s +sys 0m10.564s -CPU UTILIZATION: 22.884 / 28 +CPU UTILIZATION: 22.625 / 28 ----------------------------------------- @@ -5142,20 +5142,20 @@ CPU UTILIZATION: 22.884 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3356 assigned | 3345 processed | 81 I stole | 92 stolen from me -Node 1 (Phys 1): 3437 assigned | 3432 processed | 97 I stole | 102 stolen from me -Node 2 (Phys 2): 3453 assigned | 3458 processed | 90 I stole | 85 stolen from me -Node 3 (Phys 3): 3319 assigned | 3330 processed | 87 I stole | 76 stolen from me +Node 0 (Phys 0): 3403 assigned | 3418 processed | 104 I stole | 89 stolen from me +Node 1 (Phys 1): 3297 assigned | 3265 processed | 85 I stole | 117 stolen from me +Node 2 (Phys 2): 3419 assigned | 3426 processed | 90 I stole | 83 stolen from me +Node 3 (Phys 3): 3446 assigned | 3456 processed | 90 I stole | 80 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 355 chunks (2.6%) +Total Cross-Socket Traffic: 369 chunks (2.7%) ================================================================= -100000000 -real 0m0.992s -user 0m12.129s -sys 0m10.805s +100000454 +real 0m1.048s +user 0m12.203s +sys 0m11.260s -CPU UTILIZATION: 23.118 / 28 +CPU UTILIZATION: 22.388 / 28 ----------------------------------------- @@ -5164,19 +5164,19 @@ CPU UTILIZATION: 23.118 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.389s -user 0m0.174s -sys 0m0.704s +real 0m0.368s +user 0m0.171s +sys 0m0.686s -CPU UTILIZATION: 2.257 / 28 +CPU UTILIZATION: 2.328 / 28 ----------------------------------------- @@ -5194,11 +5194,11 @@ Total Cross-Socket Traffic: 1 chunks (0.2%) ================================================================= 0 -real 0m0.397s -user 0m0.168s -sys 0m0.716s +real 0m0.375s +user 0m0.163s +sys 0m0.713s -CPU UTILIZATION: 2.226 / 28 +CPU UTILIZATION: 2.336 / 28 ----------------------------------------- @@ -5207,19 +5207,19 @@ CPU UTILIZATION: 2.226 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3391 assigned | 3401 processed | 10 I stole | 0 stolen from me -Node 1 (Phys 1): 3393 assigned | 3389 processed | 0 I stole | 4 stolen from me -Node 2 (Phys 2): 3391 assigned | 3386 processed | 0 I stole | 5 stolen from me -Node 3 (Phys 3): 3390 assigned | 3389 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 3398 assigned | 3408 processed | 10 I stole | 0 stolen from me +Node 1 (Phys 1): 3393 assigned | 3390 processed | 2 I stole | 5 stolen from me +Node 2 (Phys 2): 3389 assigned | 3385 processed | 0 I stole | 4 stolen from me +Node 3 (Phys 3): 3385 assigned | 3382 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 11 chunks (0.1%) +Total Cross-Socket Traffic: 12 chunks (0.1%) ================================================================= -real 0m0.492s -user 0m1.706s -sys 0m1.593s +real 0m0.460s +user 0m1.683s +sys 0m1.549s -CPU UTILIZATION: 6.705 / 28 +CPU UTILIZATION: 7.026 / 28 ----------------------------------------- @@ -5228,20 +5228,20 @@ CPU UTILIZATION: 6.705 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3399 assigned | 3402 processed | 4 I stole | 1 stolen from me -Node 1 (Phys 1): 3392 assigned | 3395 processed | 4 I stole | 1 stolen from me -Node 2 (Phys 2): 3386 assigned | 3383 processed | 1 I stole | 4 stolen from me -Node 3 (Phys 3): 3388 assigned | 3385 processed | 1 I stole | 4 stolen from me +Node 0 (Phys 0): 3407 assigned | 3418 processed | 13 I stole | 2 stolen from me +Node 1 (Phys 1): 3392 assigned | 3389 processed | 3 I stole | 6 stolen from me +Node 2 (Phys 2): 3386 assigned | 3380 processed | 1 I stole | 7 stolen from me +Node 3 (Phys 3): 3380 assigned | 3378 processed | 1 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 10 chunks (0.1%) +Total Cross-Socket Traffic: 18 chunks (0.1%) ================================================================= 0 -real 0m0.476s -user 0m1.679s -sys 0m1.580s +real 0m0.443s +user 0m1.629s +sys 0m1.485s -CPU UTILIZATION: 6.846 / 28 +CPU UTILIZATION: 7.029 / 28 ----------------------------------------- @@ -5258,11 +5258,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.407s -user 0m0.626s -sys 0m1.351s +real 0m0.371s +user 0m0.629s +sys 0m1.268s -CPU UTILIZATION: 4.857 / 28 +CPU UTILIZATION: 5.113 / 28 ----------------------------------------- @@ -5280,11 +5280,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.405s -user 0m0.637s -sys 0m1.603s +real 0m0.394s +user 0m0.650s +sys 0m1.647s -CPU UTILIZATION: 5.530 / 28 +CPU UTILIZATION: 5.829 / 28 ----------------------------------------- @@ -5293,19 +5293,19 @@ CPU UTILIZATION: 5.530 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3399 assigned | 3402 processed | 11 I stole | 8 stolen from me -Node 1 (Phys 1): 3381 assigned | 3378 processed | 6 I stole | 9 stolen from me -Node 2 (Phys 2): 3404 assigned | 3401 processed | 5 I stole | 8 stolen from me -Node 3 (Phys 3): 3381 assigned | 3384 processed | 9 I stole | 6 stolen from me +Node 0 (Phys 0): 3391 assigned | 3397 processed | 10 I stole | 4 stolen from me +Node 1 (Phys 1): 3402 assigned | 3402 processed | 7 I stole | 7 stolen from me +Node 2 (Phys 2): 3386 assigned | 3381 processed | 1 I stole | 6 stolen from me +Node 3 (Phys 3): 3386 assigned | 3385 processed | 5 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 31 chunks (0.2%) +Total Cross-Socket Traffic: 23 chunks (0.2%) ================================================================= -real 0m0.717s -user 0m4.686s -sys 0m4.398s +real 0m0.720s +user 0m4.800s +sys 0m4.358s -CPU UTILIZATION: 12.669 / 28 +CPU UTILIZATION: 12.719 / 28 ----------------------------------------- @@ -5314,20 +5314,20 @@ CPU UTILIZATION: 12.669 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3411 assigned | 3401 processed | 3 I stole | 13 stolen from me -Node 1 (Phys 1): 3391 assigned | 3396 processed | 10 I stole | 5 stolen from me -Node 2 (Phys 2): 3388 assigned | 3391 processed | 8 I stole | 5 stolen from me -Node 3 (Phys 3): 3375 assigned | 3377 processed | 6 I stole | 4 stolen from me +Node 0 (Phys 0): 3404 assigned | 3394 processed | 8 I stole | 18 stolen from me +Node 1 (Phys 1): 3397 assigned | 3395 processed | 9 I stole | 11 stolen from me +Node 2 (Phys 2): 3390 assigned | 3397 processed | 17 I stole | 10 stolen from me +Node 3 (Phys 3): 3374 assigned | 3379 processed | 10 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 27 chunks (0.2%) +Total Cross-Socket Traffic: 44 chunks (0.3%) ================================================================= 100000000 -real 0m0.726s -user 0m4.767s -sys 0m4.713s +real 0m0.737s +user 0m4.818s +sys 0m4.785s -CPU UTILIZATION: 13.057 / 28 +CPU UTILIZATION: 13.029 / 28 ----------------------------------------- @@ -5345,10 +5345,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.389s -user 0m0.663s -sys 0m1.279s +user 0m0.729s +sys 0m1.366s -CPU UTILIZATION: 4.992 / 28 +CPU UTILIZATION: 5.385 / 28 ----------------------------------------- @@ -5366,11 +5366,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.393s -user 0m0.651s -sys 0m1.625s +real 0m0.403s +user 0m0.686s +sys 0m1.729s -CPU UTILIZATION: 5.791 / 28 +CPU UTILIZATION: 5.992 / 28 ----------------------------------------- @@ -5379,19 +5379,19 @@ CPU UTILIZATION: 5.791 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3400 assigned | 3397 processed | 12 I stole | 15 stolen from me -Node 1 (Phys 1): 3404 assigned | 3400 processed | 10 I stole | 14 stolen from me -Node 2 (Phys 2): 3387 assigned | 3397 processed | 16 I stole | 6 stolen from me -Node 3 (Phys 3): 3374 assigned | 3371 processed | 13 I stole | 16 stolen from me +Node 0 (Phys 0): 3393 assigned | 3399 processed | 18 I stole | 12 stolen from me +Node 1 (Phys 1): 3386 assigned | 3383 processed | 10 I stole | 13 stolen from me +Node 2 (Phys 2): 3404 assigned | 3401 processed | 7 I stole | 10 stolen from me +Node 3 (Phys 3): 3382 assigned | 3382 processed | 8 I stole | 8 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 51 chunks (0.4%) +Total Cross-Socket Traffic: 43 chunks (0.3%) ================================================================= -real 0m0.691s -user 0m4.650s -sys 0m4.104s +real 0m0.697s +user 0m4.714s +sys 0m4.111s -CPU UTILIZATION: 12.668 / 28 +CPU UTILIZATION: 12.661 / 28 ----------------------------------------- @@ -5400,20 +5400,20 @@ CPU UTILIZATION: 12.668 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3385 assigned | 3380 processed | 9 I stole | 14 stolen from me -Node 1 (Phys 1): 3401 assigned | 3405 processed | 15 I stole | 11 stolen from me -Node 2 (Phys 2): 3403 assigned | 3401 processed | 4 I stole | 6 stolen from me -Node 3 (Phys 3): 3376 assigned | 3379 processed | 7 I stole | 4 stolen from me +Node 0 (Phys 0): 3403 assigned | 3399 processed | 4 I stole | 8 stolen from me +Node 1 (Phys 1): 3400 assigned | 3396 processed | 4 I stole | 8 stolen from me +Node 2 (Phys 2): 3369 assigned | 3375 processed | 9 I stole | 3 stolen from me +Node 3 (Phys 3): 3393 assigned | 3395 processed | 6 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 35 chunks (0.3%) +Total Cross-Socket Traffic: 23 chunks (0.2%) ================================================================= 100000000 -real 0m0.701s -user 0m4.760s -sys 0m4.476s +real 0m0.711s +user 0m4.803s +sys 0m4.489s -CPU UTILIZATION: 13.175 / 28 +CPU UTILIZATION: 13.068 / 28 ----------------------------------------- @@ -5422,19 +5422,19 @@ CPU UTILIZATION: 13.175 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 110 assigned | 110 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 102 assigned | 102 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 109 assigned | 109 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 101 assigned | 101 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.770s -user 0m13.662s -sys 0m5.440s +real 0m0.805s +user 0m14.246s +sys 0m5.520s -CPU UTILIZATION: 24.807 / 28 +CPU UTILIZATION: 24.554 / 28 ----------------------------------------- @@ -5443,20 +5443,20 @@ CPU UTILIZATION: 24.807 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 102 assigned | 102 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.771s -user 0m13.523s -sys 0m5.511s +real 0m0.806s +user 0m14.338s +sys 0m5.632s -CPU UTILIZATION: 24.687 / 28 +CPU UTILIZATION: 24.776 / 28 ----------------------------------------- @@ -5465,19 +5465,19 @@ CPU UTILIZATION: 24.687 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3424 assigned | 3429 processed | 268 I stole | 263 stolen from me -Node 1 (Phys 1): 3366 assigned | 3372 processed | 230 I stole | 224 stolen from me -Node 2 (Phys 2): 3356 assigned | 3348 processed | 211 I stole | 219 stolen from me -Node 3 (Phys 3): 3419 assigned | 3416 processed | 204 I stole | 207 stolen from me +Node 0 (Phys 0): 3445 assigned | 3411 processed | 241 I stole | 275 stolen from me +Node 1 (Phys 1): 3407 assigned | 3404 processed | 240 I stole | 243 stolen from me +Node 2 (Phys 2): 3327 assigned | 3349 processed | 245 I stole | 223 stolen from me +Node 3 (Phys 3): 3386 assigned | 3401 processed | 226 I stole | 211 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 913 chunks (6.7%) +Total Cross-Socket Traffic: 952 chunks (7.0%) ================================================================= -real 0m1.011s -user 0m14.358s -sys 0m7.422s +real 0m1.021s +user 0m14.947s +sys 0m7.153s -CPU UTILIZATION: 21.543 / 28 +CPU UTILIZATION: 21.645 / 28 ----------------------------------------- @@ -5486,20 +5486,20 @@ CPU UTILIZATION: 21.543 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3412 assigned | 3367 processed | 227 I stole | 272 stolen from me -Node 1 (Phys 1): 3436 assigned | 3428 processed | 223 I stole | 231 stolen from me -Node 2 (Phys 2): 3428 assigned | 3466 processed | 238 I stole | 200 stolen from me -Node 3 (Phys 3): 3289 assigned | 3304 processed | 211 I stole | 196 stolen from me +Node 0 (Phys 0): 3429 assigned | 3384 processed | 221 I stole | 266 stolen from me +Node 1 (Phys 1): 3428 assigned | 3392 processed | 204 I stole | 240 stolen from me +Node 2 (Phys 2): 3387 assigned | 3413 processed | 218 I stole | 192 stolen from me +Node 3 (Phys 3): 3321 assigned | 3376 processed | 236 I stole | 181 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 899 chunks (6.6%) +Total Cross-Socket Traffic: 879 chunks (6.5%) ================================================================= 0 -real 0m1.017s -user 0m14.228s -sys 0m7.559s +real 0m1.047s +user 0m15.099s +sys 0m7.540s -CPU UTILIZATION: 21.422 / 28 +CPU UTILIZATION: 21.622 / 28 ----------------------------------------- @@ -5508,19 +5508,19 @@ CPU UTILIZATION: 21.422 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m5.692s -user 1m16.386s -sys 1m3.452s +real 0m5.762s +user 1m17.120s +sys 1m4.553s -CPU UTILIZATION: 24.567 / 28 +CPU UTILIZATION: 24.587 / 28 ----------------------------------------- @@ -5529,20 +5529,20 @@ CPU UTILIZATION: 24.567 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m5.706s -user 1m16.682s -sys 1m3.840s +real 0m5.788s +user 1m17.311s +sys 1m5.065s -CPU UTILIZATION: 24.627 / 28 +CPU UTILIZATION: 24.598 / 28 ----------------------------------------- @@ -5551,19 +5551,19 @@ CPU UTILIZATION: 24.627 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3393 assigned | 3393 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 3394 assigned | 3395 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 3390 assigned | 3390 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 3388 assigned | 3387 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 3395 assigned | 3396 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 3396 assigned | 3397 processed | 2 I stole | 1 stolen from me +Node 2 (Phys 2): 3389 assigned | 3387 processed | 1 I stole | 3 stolen from me +Node 3 (Phys 3): 3385 assigned | 3385 processed | 2 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.0%) +Total Cross-Socket Traffic: 7 chunks (0.1%) ================================================================= -real 0m5.708s -user 1m16.378s -sys 1m4.426s +real 0m5.783s +user 1m17.342s +sys 1m5.181s -CPU UTILIZATION: 24.667 / 28 +CPU UTILIZATION: 24.645 / 28 ----------------------------------------- @@ -5572,20 +5572,20 @@ CPU UTILIZATION: 24.667 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3400 assigned | 3400 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 3391 assigned | 3392 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 3385 assigned | 3385 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 3389 assigned | 3388 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 3394 assigned | 3395 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 3396 assigned | 3398 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 3391 assigned | 3389 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 3384 assigned | 3383 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.0%) ================================================================= 100000000 -real 0m5.751s -user 1m16.754s -sys 1m5.469s +real 0m5.823s +user 1m17.625s +sys 1m5.841s -CPU UTILIZATION: 24.730 / 28 +CPU UTILIZATION: 24.637 / 28 ----------------------------------------- @@ -5602,11 +5602,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m5.618s -user 1m16.209s -sys 1m1.888s +real 0m5.681s +user 1m16.849s +sys 1m2.749s -CPU UTILIZATION: 24.581 / 28 +CPU UTILIZATION: 24.572 / 28 ----------------------------------------- @@ -5615,20 +5615,20 @@ CPU UTILIZATION: 24.581 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m5.646s -user 1m16.105s -sys 1m2.801s +real 0m5.714s +user 1m16.951s +sys 1m3.566s -CPU UTILIZATION: 24.602 / 28 +CPU UTILIZATION: 24.591 / 28 ----------------------------------------- @@ -5637,19 +5637,19 @@ CPU UTILIZATION: 24.602 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3406 assigned | 3405 processed | 1 I stole | 2 stolen from me -Node 1 (Phys 1): 3394 assigned | 3393 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 3380 assigned | 3381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 3385 assigned | 3386 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 3397 assigned | 3399 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 3396 assigned | 3396 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 3390 assigned | 3389 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 3382 assigned | 3381 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.0%) ================================================================= -real 0m5.630s -user 1m16.321s -sys 1m2.498s +real 0m5.699s +user 1m16.931s +sys 1m3.042s -CPU UTILIZATION: 24.657 / 28 +CPU UTILIZATION: 24.560 / 28 ----------------------------------------- @@ -5658,20 +5658,20 @@ CPU UTILIZATION: 24.657 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3390 assigned | 3392 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 3396 assigned | 3396 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 3396 assigned | 3395 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 3383 assigned | 3382 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 3402 assigned | 3400 processed | 0 I stole | 2 stolen from me +Node 1 (Phys 1): 3392 assigned | 3392 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 3382 assigned | 3383 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 3389 assigned | 3390 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.0%) ================================================================= 100000000 -real 0m5.658s -user 1m16.383s -sys 1m3.392s +real 0m5.730s +user 1m17.112s +sys 1m4.154s -CPU UTILIZATION: 24.703 / 28 +CPU UTILIZATION: 24.653 / 28 ----------------------------------------- @@ -5680,19 +5680,19 @@ CPU UTILIZATION: 24.703 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.162s -user 0m0.599s -sys 0m1.139s +real 0m0.170s +user 0m0.613s +sys 0m1.143s -CPU UTILIZATION: 10.728 / 28 +CPU UTILIZATION: 10.329 / 28 ----------------------------------------- @@ -5701,20 +5701,20 @@ CPU UTILIZATION: 10.728 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 0 -real 0m0.164s -user 0m0.585s -sys 0m1.220s +real 0m0.165s +user 0m0.617s +sys 0m1.145s -CPU UTILIZATION: 11.006 / 28 +CPU UTILIZATION: 10.678 / 28 ----------------------------------------- @@ -5723,19 +5723,19 @@ CPU UTILIZATION: 11.006 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 661 assigned | 661 processed | 4 I stole | 4 stolen from me -Node 1 (Phys 1): 637 assigned | 636 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 636 assigned | 639 processed | 5 I stole | 2 stolen from me -Node 3 (Phys 3): 628 assigned | 626 processed | 1 I stole | 3 stolen from me +Node 0 (Phys 0): 654 assigned | 658 processed | 4 I stole | 0 stolen from me +Node 1 (Phys 1): 652 assigned | 652 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 629 assigned | 627 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 627 assigned | 625 processed | 1 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 11 chunks (0.4%) +Total Cross-Socket Traffic: 6 chunks (0.2%) ================================================================= -real 0m0.221s -user 0m1.519s -sys 0m1.631s +real 0m0.219s +user 0m1.522s +sys 0m1.641s -CPU UTILIZATION: 14.253 / 28 +CPU UTILIZATION: 14.442 / 28 ----------------------------------------- @@ -5744,20 +5744,20 @@ CPU UTILIZATION: 14.253 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 646 assigned | 647 processed | 3 I stole | 2 stolen from me -Node 1 (Phys 1): 639 assigned | 640 processed | 5 I stole | 4 stolen from me -Node 2 (Phys 2): 642 assigned | 643 processed | 4 I stole | 3 stolen from me -Node 3 (Phys 3): 635 assigned | 632 processed | 1 I stole | 4 stolen from me +Node 0 (Phys 0): 647 assigned | 645 processed | 4 I stole | 6 stolen from me +Node 1 (Phys 1): 634 assigned | 639 processed | 7 I stole | 2 stolen from me +Node 2 (Phys 2): 645 assigned | 644 processed | 2 I stole | 3 stolen from me +Node 3 (Phys 3): 636 assigned | 634 processed | 2 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 13 chunks (0.5%) +Total Cross-Socket Traffic: 15 chunks (0.6%) ================================================================= 0 -real 0m0.218s -user 0m1.506s -sys 0m1.644s +real 0m0.227s +user 0m1.495s +sys 0m1.693s -CPU UTILIZATION: 14.449 / 28 +CPU UTILIZATION: 14.044 / 28 ----------------------------------------- @@ -5766,19 +5766,19 @@ CPU UTILIZATION: 14.449 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.164s -user 0m0.641s -sys 0m1.379s +real 0m0.172s +user 0m0.670s +sys 0m1.369s -CPU UTILIZATION: 12.317 / 28 +CPU UTILIZATION: 11.854 / 28 ----------------------------------------- @@ -5787,8 +5787,8 @@ CPU UTILIZATION: 12.317 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -5796,11 +5796,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.192s -user 0m0.677s -sys 0m1.402s +real 0m0.195s +user 0m0.669s +sys 0m1.457s -CPU UTILIZATION: 10.828 / 28 +CPU UTILIZATION: 10.902 / 28 ----------------------------------------- @@ -5809,19 +5809,19 @@ CPU UTILIZATION: 10.828 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 663 assigned | 674 processed | 12 I stole | 1 stolen from me -Node 1 (Phys 1): 635 assigned | 627 processed | 0 I stole | 8 stolen from me -Node 2 (Phys 2): 662 assigned | 666 processed | 7 I stole | 3 stolen from me -Node 3 (Phys 3): 602 assigned | 595 processed | 2 I stole | 9 stolen from me +Node 0 (Phys 0): 653 assigned | 657 processed | 8 I stole | 4 stolen from me +Node 1 (Phys 1): 650 assigned | 651 processed | 6 I stole | 5 stolen from me +Node 2 (Phys 2): 640 assigned | 643 processed | 5 I stole | 2 stolen from me +Node 3 (Phys 3): 619 assigned | 611 processed | 2 I stole | 10 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 21 chunks (0.8%) ================================================================= -real 0m0.229s -user 0m1.582s -sys 0m1.921s +real 0m0.236s +user 0m1.566s +sys 0m1.942s -CPU UTILIZATION: 15.296 / 28 +CPU UTILIZATION: 14.864 / 28 ----------------------------------------- @@ -5830,20 +5830,20 @@ CPU UTILIZATION: 15.296 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 660 assigned | 676 processed | 20 I stole | 4 stolen from me -Node 1 (Phys 1): 630 assigned | 622 processed | 5 I stole | 13 stolen from me -Node 2 (Phys 2): 639 assigned | 641 processed | 8 I stole | 6 stolen from me -Node 3 (Phys 3): 633 assigned | 623 processed | 1 I stole | 11 stolen from me +Node 0 (Phys 0): 638 assigned | 644 processed | 8 I stole | 2 stolen from me +Node 1 (Phys 1): 642 assigned | 636 processed | 3 I stole | 9 stolen from me +Node 2 (Phys 2): 638 assigned | 632 processed | 2 I stole | 8 stolen from me +Node 3 (Phys 3): 644 assigned | 650 processed | 12 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 34 chunks (1.3%) +Total Cross-Socket Traffic: 25 chunks (1.0%) ================================================================= -3495 -real 0m0.233s -user 0m1.560s -sys 0m2.014s +3487 +real 0m0.231s +user 0m1.549s +sys 0m2.050s -CPU UTILIZATION: 15.339 / 28 +CPU UTILIZATION: 15.580 / 28 ----------------------------------------- @@ -5852,19 +5852,19 @@ CPU UTILIZATION: 15.339 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.175s -user 0m1.032s -sys 0m1.447s +real 0m0.176s +user 0m1.057s +sys 0m1.446s -CPU UTILIZATION: 14.165 / 28 +CPU UTILIZATION: 14.221 / 28 ----------------------------------------- @@ -5873,20 +5873,20 @@ CPU UTILIZATION: 14.165 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 19 assigned | 20 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -2113379 -real 0m0.206s -user 0m1.074s -sys 0m1.493s +2113621 +real 0m0.194s +user 0m1.066s +sys 0m1.548s -CPU UTILIZATION: 12.461 / 28 +CPU UTILIZATION: 13.474 / 28 ----------------------------------------- @@ -5895,19 +5895,19 @@ CPU UTILIZATION: 12.461 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 666 assigned | 676 processed | 21 I stole | 11 stolen from me -Node 1 (Phys 1): 629 assigned | 625 processed | 12 I stole | 16 stolen from me -Node 2 (Phys 2): 639 assigned | 633 processed | 9 I stole | 15 stolen from me -Node 3 (Phys 3): 628 assigned | 628 processed | 11 I stole | 11 stolen from me +Node 0 (Phys 0): 648 assigned | 648 processed | 13 I stole | 13 stolen from me +Node 1 (Phys 1): 605 assigned | 607 processed | 13 I stole | 11 stolen from me +Node 2 (Phys 2): 665 assigned | 655 processed | 9 I stole | 19 stolen from me +Node 3 (Phys 3): 644 assigned | 652 processed | 15 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 53 chunks (2.1%) +Total Cross-Socket Traffic: 50 chunks (2.0%) ================================================================= real 0m0.243s -user 0m1.698s -sys 0m2.193s +user 0m1.763s +sys 0m2.152s -CPU UTILIZATION: 16.012 / 28 +CPU UTILIZATION: 16.111 / 28 ----------------------------------------- @@ -5916,20 +5916,20 @@ CPU UTILIZATION: 16.012 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 656 assigned | 652 processed | 10 I stole | 14 stolen from me -Node 1 (Phys 1): 632 assigned | 625 processed | 12 I stole | 19 stolen from me -Node 2 (Phys 2): 634 assigned | 637 processed | 17 I stole | 14 stolen from me -Node 3 (Phys 3): 640 assigned | 648 processed | 21 I stole | 13 stolen from me +Node 0 (Phys 0): 647 assigned | 650 processed | 9 I stole | 6 stolen from me +Node 1 (Phys 1): 642 assigned | 636 processed | 11 I stole | 17 stolen from me +Node 2 (Phys 2): 615 assigned | 605 processed | 5 I stole | 15 stolen from me +Node 3 (Phys 3): 658 assigned | 671 processed | 20 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 60 chunks (2.3%) +Total Cross-Socket Traffic: 45 chunks (1.8%) ================================================================= -2113379 -real 0m0.244s -user 0m1.827s -sys 0m2.168s +2113621 +real 0m0.241s +user 0m1.753s +sys 0m2.293s -CPU UTILIZATION: 16.372 / 28 +CPU UTILIZATION: 16.788 / 28 ----------------------------------------- @@ -5938,19 +5938,19 @@ CPU UTILIZATION: 16.372 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 24 assigned | 23 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.164s -user 0m0.529s -sys 0m1.138s +real 0m0.162s +user 0m0.532s +sys 0m1.098s -CPU UTILIZATION: 10.164 / 28 +CPU UTILIZATION: 10.061 / 28 ----------------------------------------- @@ -5959,20 +5959,20 @@ CPU UTILIZATION: 10.164 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 25 processed | 2 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= 0 -real 0m0.167s -user 0m0.548s -sys 0m1.131s +real 0m0.159s +user 0m0.568s +sys 0m1.116s -CPU UTILIZATION: 10.053 / 28 +CPU UTILIZATION: 10.591 / 28 ----------------------------------------- @@ -5981,19 +5981,19 @@ CPU UTILIZATION: 10.053 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 650 processed | 4 I stole | 3 stolen from me -Node 1 (Phys 1): 640 assigned | 638 processed | 3 I stole | 5 stolen from me -Node 2 (Phys 2): 636 assigned | 636 processed | 5 I stole | 5 stolen from me -Node 3 (Phys 3): 637 assigned | 638 processed | 5 I stole | 4 stolen from me +Node 0 (Phys 0): 664 assigned | 669 processed | 6 I stole | 1 stolen from me +Node 1 (Phys 1): 643 assigned | 642 processed | 4 I stole | 5 stolen from me +Node 2 (Phys 2): 623 assigned | 620 processed | 1 I stole | 4 stolen from me +Node 3 (Phys 3): 632 assigned | 631 processed | 3 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (0.7%) +Total Cross-Socket Traffic: 14 chunks (0.5%) ================================================================= -real 0m0.221s -user 0m1.529s -sys 0m1.615s +real 0m0.214s +user 0m1.510s +sys 0m1.629s -CPU UTILIZATION: 14.226 / 28 +CPU UTILIZATION: 14.668 / 28 ----------------------------------------- @@ -6002,20 +6002,20 @@ CPU UTILIZATION: 14.226 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 648 assigned | 643 processed | 1 I stole | 6 stolen from me -Node 1 (Phys 1): 643 assigned | 645 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 624 assigned | 616 processed | 0 I stole | 8 stolen from me -Node 3 (Phys 3): 647 assigned | 658 processed | 12 I stole | 1 stolen from me +Node 0 (Phys 0): 657 assigned | 660 processed | 6 I stole | 3 stolen from me +Node 1 (Phys 1): 643 assigned | 641 processed | 4 I stole | 6 stolen from me +Node 2 (Phys 2): 625 assigned | 628 processed | 7 I stole | 4 stolen from me +Node 3 (Phys 3): 637 assigned | 633 processed | 2 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (0.7%) +Total Cross-Socket Traffic: 19 chunks (0.7%) ================================================================= 0 -real 0m0.217s -user 0m1.467s -sys 0m1.652s +real 0m0.216s +user 0m1.497s +sys 0m1.630s -CPU UTILIZATION: 14.373 / 28 +CPU UTILIZATION: 14.476 / 28 ----------------------------------------- @@ -6024,19 +6024,19 @@ CPU UTILIZATION: 14.373 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 24 processed | 3 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 18 processed | 0 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (3.7%) ================================================================= -real 0m0.165s -user 0m0.610s -sys 0m1.264s +real 0m0.164s +user 0m0.652s +sys 0m1.281s -CPU UTILIZATION: 11.357 / 28 +CPU UTILIZATION: 11.786 / 28 ----------------------------------------- @@ -6045,20 +6045,20 @@ CPU UTILIZATION: 11.357 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 24 processed | 3 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 20 assigned | 19 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (3.7%) ================================================================= -1479 -real 0m0.182s -user 0m0.593s -sys 0m1.383s +1478 +real 0m0.193s +user 0m0.658s +sys 0m1.341s -CPU UTILIZATION: 10.857 / 28 +CPU UTILIZATION: 10.357 / 28 ----------------------------------------- @@ -6067,19 +6067,19 @@ CPU UTILIZATION: 10.857 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 674 assigned | 694 processed | 30 I stole | 10 stolen from me -Node 1 (Phys 1): 650 assigned | 649 processed | 7 I stole | 8 stolen from me -Node 2 (Phys 2): 591 assigned | 573 processed | 2 I stole | 20 stolen from me -Node 3 (Phys 3): 647 assigned | 646 processed | 9 I stole | 10 stolen from me +Node 0 (Phys 0): 655 assigned | 653 processed | 4 I stole | 6 stolen from me +Node 1 (Phys 1): 652 assigned | 665 processed | 15 I stole | 2 stolen from me +Node 2 (Phys 2): 640 assigned | 634 processed | 4 I stole | 10 stolen from me +Node 3 (Phys 3): 615 assigned | 610 processed | 1 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 48 chunks (1.9%) +Total Cross-Socket Traffic: 24 chunks (0.9%) ================================================================= -real 0m0.231s -user 0m1.554s -sys 0m1.915s +real 0m0.230s +user 0m1.540s +sys 0m1.933s -CPU UTILIZATION: 15.017 / 28 +CPU UTILIZATION: 15.100 / 28 ----------------------------------------- @@ -6088,20 +6088,20 @@ CPU UTILIZATION: 15.017 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 655 assigned | 661 processed | 15 I stole | 9 stolen from me -Node 1 (Phys 1): 644 assigned | 638 processed | 4 I stole | 10 stolen from me -Node 2 (Phys 2): 646 assigned | 641 processed | 5 I stole | 10 stolen from me -Node 3 (Phys 3): 617 assigned | 622 processed | 12 I stole | 7 stolen from me +Node 0 (Phys 0): 640 assigned | 641 processed | 6 I stole | 5 stolen from me +Node 1 (Phys 1): 624 assigned | 624 processed | 6 I stole | 6 stolen from me +Node 2 (Phys 2): 647 assigned | 645 processed | 4 I stole | 6 stolen from me +Node 3 (Phys 3): 651 assigned | 652 processed | 3 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 36 chunks (1.4%) +Total Cross-Socket Traffic: 19 chunks (0.7%) ================================================================= -3460 -real 0m0.235s -user 0m1.538s -sys 0m2.038s +3459 +real 0m0.230s +user 0m1.551s +sys 0m2.039s -CPU UTILIZATION: 15.217 / 28 +CPU UTILIZATION: 15.608 / 28 ----------------------------------------- @@ -6110,19 +6110,19 @@ CPU UTILIZATION: 15.217 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 23 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 22 assigned | 20 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 18 assigned | 20 processed | 2 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 19 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (3.7%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.183s -user 0m0.994s -sys 0m1.354s +real 0m0.175s +user 0m1.021s +sys 0m1.327s -CPU UTILIZATION: 12.830 / 28 +CPU UTILIZATION: 13.417 / 28 ----------------------------------------- @@ -6131,20 +6131,20 @@ CPU UTILIZATION: 12.830 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 21 processed | 0 I stole | 2 stolen from me -Node 1 (Phys 1): 20 assigned | 22 processed | 2 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -2113379 +2113621 real 0m0.195s -user 0m0.977s -sys 0m1.455s +user 0m1.040s +sys 0m1.388s -CPU UTILIZATION: 12.471 / 28 +CPU UTILIZATION: 12.451 / 28 ----------------------------------------- @@ -6153,19 +6153,19 @@ CPU UTILIZATION: 12.471 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 659 assigned | 655 processed | 7 I stole | 11 stolen from me -Node 1 (Phys 1): 636 assigned | 643 processed | 11 I stole | 4 stolen from me -Node 2 (Phys 2): 629 assigned | 630 processed | 10 I stole | 9 stolen from me -Node 3 (Phys 3): 638 assigned | 634 processed | 4 I stole | 8 stolen from me +Node 0 (Phys 0): 636 assigned | 635 processed | 8 I stole | 9 stolen from me +Node 1 (Phys 1): 651 assigned | 662 processed | 15 I stole | 4 stolen from me +Node 2 (Phys 2): 634 assigned | 626 processed | 5 I stole | 13 stolen from me +Node 3 (Phys 3): 641 assigned | 639 processed | 10 I stole | 12 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 32 chunks (1.2%) +Total Cross-Socket Traffic: 38 chunks (1.5%) ================================================================= -real 0m0.242s -user 0m1.733s -sys 0m2.169s +real 0m0.247s +user 0m1.728s +sys 0m2.182s -CPU UTILIZATION: 16.123 / 28 +CPU UTILIZATION: 15.829 / 28 ----------------------------------------- @@ -6174,20 +6174,20 @@ CPU UTILIZATION: 16.123 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 644 assigned | 653 processed | 24 I stole | 15 stolen from me -Node 1 (Phys 1): 629 assigned | 638 processed | 24 I stole | 15 stolen from me -Node 2 (Phys 2): 638 assigned | 629 processed | 11 I stole | 20 stolen from me -Node 3 (Phys 3): 651 assigned | 642 processed | 8 I stole | 17 stolen from me +Node 0 (Phys 0): 650 assigned | 653 processed | 13 I stole | 10 stolen from me +Node 1 (Phys 1): 649 assigned | 637 processed | 8 I stole | 20 stolen from me +Node 2 (Phys 2): 640 assigned | 647 processed | 20 I stole | 13 stolen from me +Node 3 (Phys 3): 623 assigned | 625 processed | 13 I stole | 11 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 67 chunks (2.6%) +Total Cross-Socket Traffic: 54 chunks (2.1%) ================================================================= -2113379 -real 0m0.243s -user 0m1.736s -sys 0m2.261s +2113621 +real 0m0.245s +user 0m1.723s +sys 0m2.296s -CPU UTILIZATION: 16.448 / 28 +CPU UTILIZATION: 16.404 / 28 ----------------------------------------- @@ -6196,19 +6196,19 @@ CPU UTILIZATION: 16.448 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.159s -user 0m0.589s -sys 0m1.138s +real 0m0.157s +user 0m0.638s +sys 0m1.157s -CPU UTILIZATION: 10.861 / 28 +CPU UTILIZATION: 11.433 / 28 ----------------------------------------- @@ -6218,19 +6218,19 @@ CPU UTILIZATION: 10.861 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 17 assigned | 17 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.159s -user 0m0.579s -sys 0m1.160s +real 0m0.161s +user 0m0.610s +sys 0m1.145s -CPU UTILIZATION: 10.937 / 28 +CPU UTILIZATION: 10.900 / 28 ----------------------------------------- @@ -6239,19 +6239,19 @@ CPU UTILIZATION: 10.937 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 645 assigned | 649 processed | 6 I stole | 2 stolen from me -Node 1 (Phys 1): 646 assigned | 644 processed | 1 I stole | 3 stolen from me -Node 2 (Phys 2): 637 assigned | 636 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 634 assigned | 633 processed | 2 I stole | 3 stolen from me +Node 0 (Phys 0): 651 assigned | 667 processed | 18 I stole | 2 stolen from me +Node 1 (Phys 1): 644 assigned | 643 processed | 6 I stole | 7 stolen from me +Node 2 (Phys 2): 642 assigned | 633 processed | 2 I stole | 11 stolen from me +Node 3 (Phys 3): 625 assigned | 619 processed | 4 I stole | 10 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 12 chunks (0.5%) +Total Cross-Socket Traffic: 30 chunks (1.2%) ================================================================= -real 0m0.222s -user 0m1.526s -sys 0m1.614s +real 0m0.221s +user 0m1.500s +sys 0m1.677s -CPU UTILIZATION: 14.144 / 28 +CPU UTILIZATION: 14.375 / 28 ----------------------------------------- @@ -6260,20 +6260,20 @@ CPU UTILIZATION: 14.144 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 663 assigned | 664 processed | 4 I stole | 3 stolen from me -Node 1 (Phys 1): 639 assigned | 639 processed | 4 I stole | 4 stolen from me -Node 2 (Phys 2): 628 assigned | 625 processed | 4 I stole | 7 stolen from me -Node 3 (Phys 3): 632 assigned | 634 processed | 6 I stole | 4 stolen from me +Node 0 (Phys 0): 653 assigned | 653 processed | 3 I stole | 3 stolen from me +Node 1 (Phys 1): 645 assigned | 642 processed | 3 I stole | 6 stolen from me +Node 2 (Phys 2): 633 assigned | 628 processed | 1 I stole | 6 stolen from me +Node 3 (Phys 3): 631 assigned | 639 processed | 9 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 18 chunks (0.7%) +Total Cross-Socket Traffic: 16 chunks (0.6%) ================================================================= 0 -real 0m0.223s -user 0m1.527s -sys 0m1.628s +real 0m0.228s +user 0m1.520s +sys 0m1.658s -CPU UTILIZATION: 14.147 / 28 +CPU UTILIZATION: 13.938 / 28 ----------------------------------------- @@ -6282,19 +6282,19 @@ CPU UTILIZATION: 14.147 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.166s -user 0m0.657s -sys 0m1.349s +real 0m0.167s +user 0m0.613s +sys 0m1.407s -CPU UTILIZATION: 12.084 / 28 +CPU UTILIZATION: 12.095 / 28 ----------------------------------------- @@ -6303,20 +6303,20 @@ CPU UTILIZATION: 12.084 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 17 assigned | 18 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.196s -user 0m0.688s -sys 0m1.386s +real 0m0.190s +user 0m0.654s +sys 0m1.434s -CPU UTILIZATION: 10.581 / 28 +CPU UTILIZATION: 10.989 / 28 ----------------------------------------- @@ -6325,17 +6325,17 @@ CPU UTILIZATION: 10.581 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 644 assigned | 649 processed | 7 I stole | 2 stolen from me -Node 1 (Phys 1): 659 assigned | 657 processed | 4 I stole | 6 stolen from me -Node 2 (Phys 2): 631 assigned | 630 processed | 2 I stole | 3 stolen from me -Node 3 (Phys 3): 628 assigned | 626 processed | 3 I stole | 5 stolen from me +Node 0 (Phys 0): 662 assigned | 669 processed | 10 I stole | 3 stolen from me +Node 1 (Phys 1): 636 assigned | 633 processed | 1 I stole | 4 stolen from me +Node 2 (Phys 2): 630 assigned | 627 processed | 3 I stole | 6 stolen from me +Node 3 (Phys 3): 634 assigned | 633 processed | 2 I stole | 3 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 16 chunks (0.6%) ================================================================= real 0m0.239s -user 0m1.562s -sys 0m1.938s +user 0m1.550s +sys 0m1.950s CPU UTILIZATION: 14.644 / 28 @@ -6346,20 +6346,20 @@ CPU UTILIZATION: 14.644 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 639 assigned | 640 processed | 5 I stole | 4 stolen from me -Node 1 (Phys 1): 658 assigned | 659 processed | 8 I stole | 7 stolen from me -Node 2 (Phys 2): 644 assigned | 644 processed | 6 I stole | 6 stolen from me -Node 3 (Phys 3): 621 assigned | 619 processed | 2 I stole | 4 stolen from me +Node 0 (Phys 0): 652 assigned | 661 processed | 10 I stole | 1 stolen from me +Node 1 (Phys 1): 648 assigned | 644 processed | 4 I stole | 8 stolen from me +Node 2 (Phys 2): 631 assigned | 629 processed | 4 I stole | 6 stolen from me +Node 3 (Phys 3): 631 assigned | 628 processed | 3 I stole | 6 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 21 chunks (0.8%) ================================================================= -3492 -real 0m0.236s -user 0m1.579s -sys 0m2.030s +3493 +real 0m0.233s +user 0m1.572s +sys 0m2.041s -CPU UTILIZATION: 15.292 / 28 +CPU UTILIZATION: 15.506 / 28 ----------------------------------------- @@ -6370,17 +6370,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.178s -user 0m1.057s -sys 0m1.417s +real 0m0.177s +user 0m1.064s +sys 0m1.478s -CPU UTILIZATION: 13.898 / 28 +CPU UTILIZATION: 14.361 / 28 ----------------------------------------- @@ -6389,20 +6389,20 @@ CPU UTILIZATION: 13.898 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -2113379 -real 0m0.201s -user 0m1.063s -sys 0m1.458s +2113621 +real 0m0.210s +user 0m1.105s +sys 0m1.514s -CPU UTILIZATION: 12.542 / 28 +CPU UTILIZATION: 12.471 / 28 ----------------------------------------- @@ -6411,19 +6411,19 @@ CPU UTILIZATION: 12.542 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 640 assigned | 642 processed | 21 I stole | 19 stolen from me -Node 1 (Phys 1): 640 assigned | 631 processed | 16 I stole | 25 stolen from me -Node 2 (Phys 2): 663 assigned | 675 processed | 28 I stole | 16 stolen from me -Node 3 (Phys 3): 619 assigned | 614 processed | 13 I stole | 18 stolen from me +Node 0 (Phys 0): 628 assigned | 632 processed | 11 I stole | 7 stolen from me +Node 1 (Phys 1): 642 assigned | 638 processed | 8 I stole | 12 stolen from me +Node 2 (Phys 2): 648 assigned | 639 processed | 3 I stole | 12 stolen from me +Node 3 (Phys 3): 644 assigned | 653 processed | 13 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 78 chunks (3.0%) +Total Cross-Socket Traffic: 35 chunks (1.4%) ================================================================= -real 0m0.255s -user 0m1.720s -sys 0m2.191s +real 0m0.245s +user 0m1.739s +sys 0m2.214s -CPU UTILIZATION: 15.337 / 28 +CPU UTILIZATION: 16.134 / 28 ----------------------------------------- @@ -6432,20 +6432,20 @@ CPU UTILIZATION: 15.337 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 627 assigned | 618 processed | 9 I stole | 18 stolen from me -Node 1 (Phys 1): 638 assigned | 624 processed | 8 I stole | 22 stolen from me -Node 2 (Phys 2): 645 assigned | 661 processed | 25 I stole | 9 stolen from me -Node 3 (Phys 3): 652 assigned | 659 processed | 17 I stole | 10 stolen from me +Node 0 (Phys 0): 646 assigned | 652 processed | 16 I stole | 10 stolen from me +Node 1 (Phys 1): 637 assigned | 628 processed | 6 I stole | 15 stolen from me +Node 2 (Phys 2): 633 assigned | 633 processed | 10 I stole | 10 stolen from me +Node 3 (Phys 3): 646 assigned | 649 processed | 12 I stole | 9 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 59 chunks (2.3%) +Total Cross-Socket Traffic: 44 chunks (1.7%) ================================================================= -2113379 +2113621 real 0m0.245s -user 0m1.778s -sys 0m2.239s +user 0m1.777s +sys 0m2.258s -CPU UTILIZATION: 16.395 / 28 +CPU UTILIZATION: 16.469 / 28 ----------------------------------------- @@ -6455,18 +6455,18 @@ CPU UTILIZATION: 16.395 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 17 assigned | 18 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.164s -user 0m0.544s -sys 0m1.072s +real 0m0.158s +user 0m0.555s +sys 0m1.102s -CPU UTILIZATION: 9.853 / 28 +CPU UTILIZATION: 10.487 / 28 ----------------------------------------- @@ -6475,20 +6475,20 @@ CPU UTILIZATION: 9.853 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 25 assigned | 26 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 1 I stole | 1 stolen from me +Node 3 (Phys 3): 16 assigned | 16 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= 0 -real 0m0.158s -user 0m0.562s -sys 0m1.108s +real 0m0.160s +user 0m0.545s +sys 0m1.105s -CPU UTILIZATION: 10.569 / 28 +CPU UTILIZATION: 10.312 / 28 ----------------------------------------- @@ -6497,19 +6497,19 @@ CPU UTILIZATION: 10.569 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 641 assigned | 648 processed | 8 I stole | 1 stolen from me -Node 1 (Phys 1): 646 assigned | 645 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 643 assigned | 641 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 632 assigned | 628 processed | 2 I stole | 6 stolen from me +Node 0 (Phys 0): 630 assigned | 632 processed | 4 I stole | 2 stolen from me +Node 1 (Phys 1): 648 assigned | 650 processed | 6 I stole | 4 stolen from me +Node 2 (Phys 2): 649 assigned | 643 processed | 1 I stole | 7 stolen from me +Node 3 (Phys 3): 635 assigned | 637 processed | 4 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 13 chunks (0.5%) +Total Cross-Socket Traffic: 15 chunks (0.6%) ================================================================= real 0m0.222s -user 0m1.495s -sys 0m1.639s +user 0m1.507s +sys 0m1.661s -CPU UTILIZATION: 14.117 / 28 +CPU UTILIZATION: 14.270 / 28 ----------------------------------------- @@ -6518,20 +6518,20 @@ CPU UTILIZATION: 14.117 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 651 assigned | 661 processed | 15 I stole | 5 stolen from me -Node 1 (Phys 1): 640 assigned | 644 processed | 8 I stole | 4 stolen from me -Node 2 (Phys 2): 636 assigned | 630 processed | 0 I stole | 6 stolen from me -Node 3 (Phys 3): 635 assigned | 627 processed | 0 I stole | 8 stolen from me +Node 0 (Phys 0): 639 assigned | 638 processed | 4 I stole | 5 stolen from me +Node 1 (Phys 1): 639 assigned | 645 processed | 7 I stole | 1 stolen from me +Node 2 (Phys 2): 646 assigned | 644 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 638 assigned | 635 processed | 1 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 23 chunks (0.9%) +Total Cross-Socket Traffic: 12 chunks (0.5%) ================================================================= 0 -real 0m0.227s -user 0m1.504s -sys 0m1.639s +real 0m0.220s +user 0m1.501s +sys 0m1.656s -CPU UTILIZATION: 13.845 / 28 +CPU UTILIZATION: 14.350 / 28 ----------------------------------------- @@ -6540,19 +6540,19 @@ CPU UTILIZATION: 13.845 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 20 processed | 0 I stole | 2 stolen from me -Node 1 (Phys 1): 21 assigned | 23 processed | 2 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 21 assigned | 23 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (3.7%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= real 0m0.166s user 0m0.610s -sys 0m1.305s +sys 0m1.293s -CPU UTILIZATION: 11.536 / 28 +CPU UTILIZATION: 11.463 / 28 ----------------------------------------- @@ -6562,19 +6562,19 @@ CPU UTILIZATION: 11.536 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -1478 -real 0m0.190s -user 0m0.633s -sys 0m1.347s +1477 +real 0m0.193s +user 0m0.608s +sys 0m1.368s -CPU UTILIZATION: 10.421 / 28 +CPU UTILIZATION: 10.238 / 28 ----------------------------------------- @@ -6583,19 +6583,19 @@ CPU UTILIZATION: 10.421 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 646 assigned | 649 processed | 4 I stole | 1 stolen from me -Node 1 (Phys 1): 641 assigned | 638 processed | 3 I stole | 6 stolen from me -Node 2 (Phys 2): 640 assigned | 639 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 635 assigned | 636 processed | 5 I stole | 4 stolen from me +Node 0 (Phys 0): 660 assigned | 660 processed | 7 I stole | 7 stolen from me +Node 1 (Phys 1): 638 assigned | 637 processed | 3 I stole | 4 stolen from me +Node 2 (Phys 2): 622 assigned | 618 processed | 1 I stole | 5 stolen from me +Node 3 (Phys 3): 642 assigned | 647 processed | 6 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 15 chunks (0.6%) +Total Cross-Socket Traffic: 17 chunks (0.7%) ================================================================= real 0m0.236s -user 0m1.588s -sys 0m1.883s +user 0m1.586s +sys 0m1.915s -CPU UTILIZATION: 14.707 / 28 +CPU UTILIZATION: 14.834 / 28 ----------------------------------------- @@ -6604,20 +6604,20 @@ CPU UTILIZATION: 14.707 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 647 assigned | 651 processed | 7 I stole | 3 stolen from me -Node 1 (Phys 1): 645 assigned | 646 processed | 6 I stole | 5 stolen from me -Node 2 (Phys 2): 634 assigned | 631 processed | 3 I stole | 6 stolen from me -Node 3 (Phys 3): 636 assigned | 634 processed | 4 I stole | 6 stolen from me +Node 0 (Phys 0): 666 assigned | 667 processed | 5 I stole | 4 stolen from me +Node 1 (Phys 1): 643 assigned | 645 processed | 7 I stole | 5 stolen from me +Node 2 (Phys 2): 617 assigned | 616 processed | 5 I stole | 6 stolen from me +Node 3 (Phys 3): 636 assigned | 634 processed | 2 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 20 chunks (0.8%) +Total Cross-Socket Traffic: 19 chunks (0.7%) ================================================================= -3462 -real 0m0.233s -user 0m1.562s -sys 0m2.002s +3460 +real 0m0.236s +user 0m1.545s +sys 0m2.034s -CPU UTILIZATION: 15.296 / 28 +CPU UTILIZATION: 15.165 / 28 ----------------------------------------- @@ -6626,19 +6626,19 @@ CPU UTILIZATION: 15.296 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 17 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 18 assigned | 20 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= real 0m0.179s -user 0m0.980s -sys 0m1.381s +user 0m1.040s +sys 0m1.292s -CPU UTILIZATION: 13.189 / 28 +CPU UTILIZATION: 13.027 / 28 ----------------------------------------- @@ -6647,20 +6647,20 @@ CPU UTILIZATION: 13.189 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m0.206s -user 0m1.032s -sys 0m1.382s +2113621 +real 0m0.202s +user 0m1.002s +sys 0m1.391s -CPU UTILIZATION: 11.718 / 28 +CPU UTILIZATION: 11.846 / 28 ----------------------------------------- @@ -6669,19 +6669,19 @@ CPU UTILIZATION: 11.718 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 651 assigned | 653 processed | 15 I stole | 13 stolen from me -Node 1 (Phys 1): 632 assigned | 625 processed | 12 I stole | 19 stolen from me -Node 2 (Phys 2): 637 assigned | 647 processed | 21 I stole | 11 stolen from me -Node 3 (Phys 3): 642 assigned | 637 processed | 14 I stole | 19 stolen from me +Node 0 (Phys 0): 647 assigned | 649 processed | 17 I stole | 15 stolen from me +Node 1 (Phys 1): 683 assigned | 697 processed | 28 I stole | 14 stolen from me +Node 2 (Phys 2): 649 assigned | 657 processed | 23 I stole | 15 stolen from me +Node 3 (Phys 3): 583 assigned | 559 processed | 3 I stole | 27 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 62 chunks (2.4%) +Total Cross-Socket Traffic: 71 chunks (2.8%) ================================================================= -real 0m0.253s -user 0m1.710s -sys 0m2.179s +real 0m0.246s +user 0m1.753s +sys 0m2.181s -CPU UTILIZATION: 15.371 / 28 +CPU UTILIZATION: 15.991 / 28 ----------------------------------------- @@ -6690,20 +6690,20 @@ CPU UTILIZATION: 15.371 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 686 assigned | 691 processed | 14 I stole | 9 stolen from me -Node 1 (Phys 1): 606 assigned | 616 processed | 21 I stole | 11 stolen from me -Node 2 (Phys 2): 640 assigned | 626 processed | 10 I stole | 24 stolen from me -Node 3 (Phys 3): 630 assigned | 629 processed | 16 I stole | 17 stolen from me +Node 0 (Phys 0): 659 assigned | 664 processed | 17 I stole | 12 stolen from me +Node 1 (Phys 1): 625 assigned | 637 processed | 21 I stole | 9 stolen from me +Node 2 (Phys 2): 642 assigned | 629 processed | 8 I stole | 21 stolen from me +Node 3 (Phys 3): 636 assigned | 632 processed | 9 I stole | 13 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 61 chunks (2.4%) +Total Cross-Socket Traffic: 55 chunks (2.1%) ================================================================= -2113379 -real 0m0.245s -user 0m1.762s -sys 0m2.221s +2113621 +real 0m0.244s +user 0m1.754s +sys 0m2.251s -CPU UTILIZATION: 16.257 / 28 +CPU UTILIZATION: 16.413 / 28 ----------------------------------------- @@ -6712,19 +6712,19 @@ CPU UTILIZATION: 16.257 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 23 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 21 assigned | 23 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 18 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 4 chunks (4.9%) ================================================================= -real 0m0.159s -user 0m0.563s -sys 0m1.122s +real 0m0.163s +user 0m0.608s +sys 0m1.090s -CPU UTILIZATION: 10.597 / 28 +CPU UTILIZATION: 10.417 / 28 ----------------------------------------- @@ -6733,20 +6733,20 @@ CPU UTILIZATION: 10.597 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.157s -user 0m0.541s -sys 0m1.139s +real 0m0.159s +user 0m0.587s +sys 0m1.180s -CPU UTILIZATION: 10.700 / 28 +CPU UTILIZATION: 11.113 / 28 ----------------------------------------- @@ -6755,19 +6755,19 @@ CPU UTILIZATION: 10.700 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 647 assigned | 649 processed | 6 I stole | 4 stolen from me -Node 1 (Phys 1): 640 assigned | 643 processed | 7 I stole | 4 stolen from me -Node 2 (Phys 2): 638 assigned | 636 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 637 assigned | 634 processed | 1 I stole | 4 stolen from me +Node 0 (Phys 0): 649 assigned | 653 processed | 5 I stole | 1 stolen from me +Node 1 (Phys 1): 663 assigned | 663 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 623 assigned | 620 processed | 0 I stole | 3 stolen from me +Node 3 (Phys 3): 627 assigned | 626 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 16 chunks (0.6%) +Total Cross-Socket Traffic: 8 chunks (0.3%) ================================================================= -real 0m0.215s -user 0m1.451s -sys 0m1.579s +real 0m0.218s +user 0m1.448s +sys 0m1.578s -CPU UTILIZATION: 14.093 / 28 +CPU UTILIZATION: 13.880 / 28 ----------------------------------------- @@ -6776,20 +6776,20 @@ CPU UTILIZATION: 14.093 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 653 assigned | 663 processed | 11 I stole | 1 stolen from me -Node 1 (Phys 1): 633 assigned | 633 processed | 4 I stole | 4 stolen from me -Node 2 (Phys 2): 633 assigned | 627 processed | 1 I stole | 7 stolen from me -Node 3 (Phys 3): 643 assigned | 639 processed | 0 I stole | 4 stolen from me +Node 0 (Phys 0): 638 assigned | 645 processed | 9 I stole | 2 stolen from me +Node 1 (Phys 1): 642 assigned | 645 processed | 6 I stole | 3 stolen from me +Node 2 (Phys 2): 651 assigned | 645 processed | 0 I stole | 6 stolen from me +Node 3 (Phys 3): 631 assigned | 627 processed | 1 I stole | 5 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 16 chunks (0.6%) ================================================================= 0 -real 0m0.212s -user 0m1.444s -sys 0m1.570s +real 0m0.214s +user 0m1.463s +sys 0m1.593s -CPU UTILIZATION: 14.216 / 28 +CPU UTILIZATION: 14.280 / 28 ----------------------------------------- @@ -6798,19 +6798,19 @@ CPU UTILIZATION: 14.216 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.158s -user 0m0.613s -sys 0m1.237s +real 0m0.165s +user 0m0.620s +sys 0m1.266s -CPU UTILIZATION: 11.708 / 28 +CPU UTILIZATION: 11.430 / 28 ----------------------------------------- @@ -6819,20 +6819,20 @@ CPU UTILIZATION: 11.708 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.178s -user 0m0.605s -sys 0m1.927s +real 0m0.180s +user 0m0.666s +sys 0m1.863s -CPU UTILIZATION: 14.224 / 28 +CPU UTILIZATION: 14.050 / 28 ----------------------------------------- @@ -6841,19 +6841,19 @@ CPU UTILIZATION: 14.224 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 663 assigned | 666 processed | 6 I stole | 3 stolen from me -Node 1 (Phys 1): 632 assigned | 633 processed | 5 I stole | 4 stolen from me -Node 2 (Phys 2): 618 assigned | 613 processed | 1 I stole | 6 stolen from me -Node 3 (Phys 3): 649 assigned | 650 processed | 5 I stole | 4 stolen from me +Node 0 (Phys 0): 643 assigned | 643 processed | 6 I stole | 6 stolen from me +Node 1 (Phys 1): 652 assigned | 654 processed | 8 I stole | 6 stolen from me +Node 2 (Phys 2): 644 assigned | 649 processed | 8 I stole | 3 stolen from me +Node 3 (Phys 3): 623 assigned | 616 processed | 2 I stole | 9 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (0.7%) +Total Cross-Socket Traffic: 24 chunks (0.9%) ================================================================= -real 0m0.219s -user 0m1.509s -sys 0m1.710s +real 0m0.224s +user 0m1.532s +sys 0m1.683s -CPU UTILIZATION: 14.698 / 28 +CPU UTILIZATION: 14.352 / 28 ----------------------------------------- @@ -6862,20 +6862,20 @@ CPU UTILIZATION: 14.698 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 650 processed | 4 I stole | 3 stolen from me -Node 1 (Phys 1): 641 assigned | 638 processed | 4 I stole | 7 stolen from me -Node 2 (Phys 2): 638 assigned | 640 processed | 4 I stole | 2 stolen from me -Node 3 (Phys 3): 634 assigned | 634 processed | 4 I stole | 4 stolen from me +Node 0 (Phys 0): 647 assigned | 653 processed | 8 I stole | 2 stolen from me +Node 1 (Phys 1): 642 assigned | 644 processed | 5 I stole | 3 stolen from me +Node 2 (Phys 2): 638 assigned | 637 processed | 4 I stole | 5 stolen from me +Node 3 (Phys 3): 635 assigned | 628 processed | 1 I stole | 8 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 16 chunks (0.6%) +Total Cross-Socket Traffic: 18 chunks (0.7%) ================================================================= -3490 -real 0m0.227s -user 0m1.496s -sys 0m1.945s +3494 +real 0m0.230s +user 0m1.520s +sys 0m1.921s -CPU UTILIZATION: 15.158 / 28 +CPU UTILIZATION: 14.960 / 28 ----------------------------------------- @@ -6884,19 +6884,19 @@ CPU UTILIZATION: 15.158 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.171s -user 0m0.957s -sys 0m1.305s +real 0m0.167s +user 0m1.032s +sys 0m1.299s -CPU UTILIZATION: 13.228 / 28 +CPU UTILIZATION: 13.958 / 28 ----------------------------------------- @@ -6906,19 +6906,19 @@ CPU UTILIZATION: 13.228 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m0.184s -user 0m0.991s -sys 0m1.748s +2113621 +real 0m0.190s +user 0m1.041s +sys 0m1.822s -CPU UTILIZATION: 14.885 / 28 +CPU UTILIZATION: 15.068 / 28 ----------------------------------------- @@ -6927,19 +6927,19 @@ CPU UTILIZATION: 14.885 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 651 assigned | 652 processed | 18 I stole | 17 stolen from me -Node 1 (Phys 1): 643 assigned | 634 processed | 7 I stole | 16 stolen from me -Node 2 (Phys 2): 640 assigned | 646 processed | 16 I stole | 10 stolen from me -Node 3 (Phys 3): 628 assigned | 630 processed | 14 I stole | 12 stolen from me +Node 0 (Phys 0): 652 assigned | 652 processed | 9 I stole | 9 stolen from me +Node 1 (Phys 1): 646 assigned | 642 processed | 6 I stole | 10 stolen from me +Node 2 (Phys 2): 633 assigned | 631 processed | 10 I stole | 12 stolen from me +Node 3 (Phys 3): 631 assigned | 637 processed | 13 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 55 chunks (2.1%) +Total Cross-Socket Traffic: 38 chunks (1.5%) ================================================================= -real 0m0.229s -user 0m1.658s -sys 0m1.951s +real 0m0.235s +user 0m1.706s +sys 0m1.988s -CPU UTILIZATION: 15.759 / 28 +CPU UTILIZATION: 15.719 / 28 ----------------------------------------- @@ -6948,20 +6948,20 @@ CPU UTILIZATION: 15.759 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 658 assigned | 654 processed | 15 I stole | 19 stolen from me -Node 1 (Phys 1): 618 assigned | 615 processed | 12 I stole | 15 stolen from me -Node 2 (Phys 2): 636 assigned | 630 processed | 11 I stole | 17 stolen from me -Node 3 (Phys 3): 650 assigned | 663 processed | 24 I stole | 11 stolen from me +Node 0 (Phys 0): 650 assigned | 659 processed | 12 I stole | 3 stolen from me +Node 1 (Phys 1): 641 assigned | 640 processed | 8 I stole | 9 stolen from me +Node 2 (Phys 2): 618 assigned | 615 processed | 5 I stole | 8 stolen from me +Node 3 (Phys 3): 653 assigned | 648 processed | 3 I stole | 8 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 62 chunks (2.4%) +Total Cross-Socket Traffic: 28 chunks (1.1%) ================================================================= -2113379 -real 0m0.233s -user 0m1.715s -sys 0m2.075s +2113621 +real 0m0.241s +user 0m1.661s +sys 0m2.178s -CPU UTILIZATION: 16.266 / 28 +CPU UTILIZATION: 15.929 / 28 ----------------------------------------- @@ -6970,19 +6970,19 @@ CPU UTILIZATION: 16.266 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.163s -user 0m0.519s -sys 0m1.093s +real 0m0.162s +user 0m0.533s +sys 0m1.106s -CPU UTILIZATION: 9.889 / 28 +CPU UTILIZATION: 10.117 / 28 ----------------------------------------- @@ -7000,11 +7000,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.163s -user 0m0.534s -sys 0m1.105s +real 0m0.161s +user 0m0.513s +sys 0m1.079s -CPU UTILIZATION: 10.055 / 28 +CPU UTILIZATION: 9.888 / 28 ----------------------------------------- @@ -7013,19 +7013,19 @@ CPU UTILIZATION: 10.055 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 654 assigned | 658 processed | 7 I stole | 3 stolen from me -Node 1 (Phys 1): 637 assigned | 632 processed | 2 I stole | 7 stolen from me -Node 2 (Phys 2): 632 assigned | 627 processed | 0 I stole | 5 stolen from me -Node 3 (Phys 3): 639 assigned | 645 processed | 8 I stole | 2 stolen from me +Node 0 (Phys 0): 662 assigned | 666 processed | 6 I stole | 2 stolen from me +Node 1 (Phys 1): 638 assigned | 639 processed | 3 I stole | 2 stolen from me +Node 2 (Phys 2): 625 assigned | 620 processed | 0 I stole | 5 stolen from me +Node 3 (Phys 3): 637 assigned | 637 processed | 4 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (0.7%) +Total Cross-Socket Traffic: 13 chunks (0.5%) ================================================================= real 0m0.216s -user 0m1.425s -sys 0m1.609s +user 0m1.459s +sys 0m1.563s -CPU UTILIZATION: 14.046 / 28 +CPU UTILIZATION: 13.990 / 28 ----------------------------------------- @@ -7034,20 +7034,20 @@ CPU UTILIZATION: 14.046 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 655 assigned | 659 processed | 8 I stole | 4 stolen from me -Node 1 (Phys 1): 634 assigned | 633 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 639 assigned | 639 processed | 2 I stole | 2 stolen from me -Node 3 (Phys 3): 634 assigned | 631 processed | 3 I stole | 6 stolen from me +Node 0 (Phys 0): 653 assigned | 656 processed | 5 I stole | 2 stolen from me +Node 1 (Phys 1): 630 assigned | 630 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 635 assigned | 635 processed | 2 I stole | 2 stolen from me +Node 3 (Phys 3): 644 assigned | 641 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 15 chunks (0.6%) +Total Cross-Socket Traffic: 8 chunks (0.3%) ================================================================= 0 -real 0m0.211s -user 0m1.461s -sys 0m1.539s +real 0m0.214s +user 0m1.466s +sys 0m1.562s -CPU UTILIZATION: 14.218 / 28 +CPU UTILIZATION: 14.149 / 28 ----------------------------------------- @@ -7056,19 +7056,19 @@ CPU UTILIZATION: 14.218 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 18 assigned | 17 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.161s -user 0m0.574s -sys 0m1.140s +real 0m0.159s +user 0m0.564s +sys 0m1.193s -CPU UTILIZATION: 10.645 / 28 +CPU UTILIZATION: 11.050 / 28 ----------------------------------------- @@ -7077,20 +7077,20 @@ CPU UTILIZATION: 10.645 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -1477 -real 0m0.176s -user 0m0.592s -sys 0m1.831s +1478 +real 0m0.178s +user 0m0.620s +sys 0m1.862s -CPU UTILIZATION: 13.767 / 28 +CPU UTILIZATION: 13.943 / 28 ----------------------------------------- @@ -7099,19 +7099,19 @@ CPU UTILIZATION: 13.767 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 659 assigned | 662 processed | 5 I stole | 2 stolen from me -Node 1 (Phys 1): 647 assigned | 646 processed | 3 I stole | 4 stolen from me -Node 2 (Phys 2): 626 assigned | 619 processed | 0 I stole | 7 stolen from me -Node 3 (Phys 3): 630 assigned | 635 processed | 5 I stole | 0 stolen from me +Node 0 (Phys 0): 637 assigned | 652 processed | 20 I stole | 5 stolen from me +Node 1 (Phys 1): 636 assigned | 625 processed | 7 I stole | 18 stolen from me +Node 2 (Phys 2): 649 assigned | 644 processed | 6 I stole | 11 stolen from me +Node 3 (Phys 3): 640 assigned | 641 processed | 8 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 13 chunks (0.5%) +Total Cross-Socket Traffic: 41 chunks (1.6%) ================================================================= -real 0m0.223s -user 0m1.462s -sys 0m1.755s +real 0m0.220s +user 0m1.506s +sys 0m1.712s -CPU UTILIZATION: 14.426 / 28 +CPU UTILIZATION: 14.627 / 28 ----------------------------------------- @@ -7120,20 +7120,20 @@ CPU UTILIZATION: 14.426 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 648 assigned | 652 processed | 10 I stole | 6 stolen from me -Node 1 (Phys 1): 647 assigned | 647 processed | 7 I stole | 7 stolen from me -Node 2 (Phys 2): 644 assigned | 646 processed | 8 I stole | 6 stolen from me -Node 3 (Phys 3): 623 assigned | 617 processed | 5 I stole | 11 stolen from me +Node 0 (Phys 0): 659 assigned | 672 processed | 21 I stole | 8 stolen from me +Node 1 (Phys 1): 663 assigned | 674 processed | 19 I stole | 8 stolen from me +Node 2 (Phys 2): 628 assigned | 611 processed | 5 I stole | 22 stolen from me +Node 3 (Phys 3): 612 assigned | 605 processed | 4 I stole | 11 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 30 chunks (1.2%) +Total Cross-Socket Traffic: 49 chunks (1.9%) ================================================================= -3460 -real 0m0.228s -user 0m1.443s -sys 0m1.961s +3464 +real 0m0.229s +user 0m1.489s +sys 0m1.862s -CPU UTILIZATION: 14.929 / 28 +CPU UTILIZATION: 14.633 / 28 ----------------------------------------- @@ -7142,19 +7142,19 @@ CPU UTILIZATION: 14.929 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.172s +real 0m0.171s user 0m0.959s -sys 0m1.222s +sys 0m1.242s -CPU UTILIZATION: 12.680 / 28 +CPU UTILIZATION: 12.871 / 28 ----------------------------------------- @@ -7163,20 +7163,20 @@ CPU UTILIZATION: 12.680 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 22 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 18 assigned | 19 processed | 1 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -2113379 -real 0m0.188s -user 0m0.973s -sys 0m1.693s +2113621 +real 0m0.185s +user 0m0.986s +sys 0m1.599s -CPU UTILIZATION: 14.180 / 28 +CPU UTILIZATION: 13.972 / 28 ----------------------------------------- @@ -7185,19 +7185,19 @@ CPU UTILIZATION: 14.180 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 653 assigned | 663 processed | 17 I stole | 7 stolen from me -Node 1 (Phys 1): 647 assigned | 650 processed | 11 I stole | 8 stolen from me -Node 2 (Phys 2): 654 assigned | 647 processed | 2 I stole | 9 stolen from me -Node 3 (Phys 3): 608 assigned | 602 processed | 6 I stole | 12 stolen from me +Node 0 (Phys 0): 647 assigned | 642 processed | 3 I stole | 8 stolen from me +Node 1 (Phys 1): 654 assigned | 666 processed | 16 I stole | 4 stolen from me +Node 2 (Phys 2): 634 assigned | 636 processed | 6 I stole | 4 stolen from me +Node 3 (Phys 3): 627 assigned | 618 processed | 5 I stole | 14 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 36 chunks (1.4%) +Total Cross-Socket Traffic: 30 chunks (1.2%) ================================================================= -real 0m0.230s -user 0m1.665s +real 0m0.232s +user 0m1.710s sys 0m1.945s -CPU UTILIZATION: 15.695 / 28 +CPU UTILIZATION: 15.754 / 28 ----------------------------------------- @@ -7206,20 +7206,20 @@ CPU UTILIZATION: 15.695 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 637 assigned | 634 processed | 10 I stole | 13 stolen from me -Node 1 (Phys 1): 660 assigned | 664 processed | 16 I stole | 12 stolen from me -Node 2 (Phys 2): 648 assigned | 647 processed | 12 I stole | 13 stolen from me -Node 3 (Phys 3): 617 assigned | 617 processed | 8 I stole | 8 stolen from me +Node 0 (Phys 0): 645 assigned | 653 processed | 19 I stole | 11 stolen from me +Node 1 (Phys 1): 652 assigned | 653 processed | 17 I stole | 16 stolen from me +Node 2 (Phys 2): 645 assigned | 637 processed | 10 I stole | 18 stolen from me +Node 3 (Phys 3): 620 assigned | 619 processed | 12 I stole | 13 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 46 chunks (1.8%) +Total Cross-Socket Traffic: 58 chunks (2.3%) ================================================================= -2113379 -real 0m0.236s -user 0m1.740s -sys 0m2.049s +2113621 +real 0m0.239s +user 0m1.727s +sys 0m2.064s -CPU UTILIZATION: 16.055 / 28 +CPU UTILIZATION: 15.861 / 28 ----------------------------------------- @@ -7236,11 +7236,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.356s -user 0m7.115s -sys 0m0.399s +real 0m0.360s +user 0m7.173s +sys 0m0.405s -CPU UTILIZATION: 21.106 / 28 +CPU UTILIZATION: 21.050 / 28 ----------------------------------------- @@ -7249,20 +7249,20 @@ CPU UTILIZATION: 21.106 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.359s -user 0m7.177s -sys 0m0.417s +real 0m0.358s +user 0m7.207s +sys 0m0.389s -CPU UTILIZATION: 21.153 / 28 +CPU UTILIZATION: 21.217 / 28 ----------------------------------------- @@ -7271,19 +7271,19 @@ CPU UTILIZATION: 21.153 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 655 assigned | 670 processed | 110 I stole | 95 stolen from me -Node 1 (Phys 1): 695 assigned | 643 processed | 59 I stole | 111 stolen from me -Node 2 (Phys 2): 632 assigned | 656 processed | 82 I stole | 58 stolen from me -Node 3 (Phys 3): 580 assigned | 593 processed | 91 I stole | 78 stolen from me +Node 0 (Phys 0): 687 assigned | 673 processed | 62 I stole | 76 stolen from me +Node 1 (Phys 1): 687 assigned | 678 processed | 83 I stole | 92 stolen from me +Node 2 (Phys 2): 571 assigned | 645 processed | 122 I stole | 48 stolen from me +Node 3 (Phys 3): 617 assigned | 566 processed | 59 I stole | 110 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 342 chunks (13.3%) +Total Cross-Socket Traffic: 326 chunks (12.7%) ================================================================= -real 0m0.351s -user 0m6.994s -sys 0m0.384s +real 0m0.352s +user 0m6.936s +sys 0m0.408s -CPU UTILIZATION: 21.019 / 28 +CPU UTILIZATION: 20.863 / 28 ----------------------------------------- @@ -7292,20 +7292,20 @@ CPU UTILIZATION: 21.019 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 634 assigned | 633 processed | 59 I stole | 60 stolen from me -Node 1 (Phys 1): 648 assigned | 661 processed | 59 I stole | 46 stolen from me -Node 2 (Phys 2): 663 assigned | 658 processed | 53 I stole | 58 stolen from me -Node 3 (Phys 3): 617 assigned | 610 processed | 53 I stole | 60 stolen from me +Node 0 (Phys 0): 661 assigned | 672 processed | 83 I stole | 72 stolen from me +Node 1 (Phys 1): 633 assigned | 626 processed | 74 I stole | 81 stolen from me +Node 2 (Phys 2): 626 assigned | 636 processed | 79 I stole | 69 stolen from me +Node 3 (Phys 3): 642 assigned | 628 processed | 65 I stole | 79 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 224 chunks (8.7%) +Total Cross-Socket Traffic: 301 chunks (11.7%) ================================================================= 0 -real 0m0.349s -user 0m6.938s -sys 0m0.399s +real 0m0.350s +user 0m7.019s +sys 0m0.409s -CPU UTILIZATION: 21.022 / 28 +CPU UTILIZATION: 21.222 / 28 ----------------------------------------- @@ -7322,11 +7322,11 @@ Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.378s -user 0m7.549s -sys 0m0.486s +real 0m0.380s +user 0m7.599s +sys 0m0.513s -CPU UTILIZATION: 21.256 / 28 +CPU UTILIZATION: 21.347 / 28 ----------------------------------------- @@ -7344,11 +7344,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.379s -user 0m7.603s -sys 0m0.547s +real 0m0.378s +user 0m7.598s +sys 0m0.574s -CPU UTILIZATION: 21.503 / 28 +CPU UTILIZATION: 21.619 / 28 ----------------------------------------- @@ -7357,19 +7357,19 @@ CPU UTILIZATION: 21.503 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 690 assigned | 674 processed | 64 I stole | 80 stolen from me -Node 1 (Phys 1): 569 assigned | 595 processed | 98 I stole | 72 stolen from me -Node 2 (Phys 2): 630 assigned | 637 processed | 77 I stole | 70 stolen from me -Node 3 (Phys 3): 673 assigned | 656 processed | 45 I stole | 62 stolen from me +Node 0 (Phys 0): 655 assigned | 649 processed | 47 I stole | 53 stolen from me +Node 1 (Phys 1): 646 assigned | 652 processed | 60 I stole | 54 stolen from me +Node 2 (Phys 2): 648 assigned | 646 processed | 41 I stole | 43 stolen from me +Node 3 (Phys 3): 613 assigned | 615 processed | 49 I stole | 47 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 284 chunks (11.1%) +Total Cross-Socket Traffic: 197 chunks (7.7%) ================================================================= -real 0m0.367s -user 0m7.372s -sys 0m0.530s +real 0m0.373s +user 0m7.188s +sys 0m0.564s -CPU UTILIZATION: 21.531 / 28 +CPU UTILIZATION: 20.782 / 28 ----------------------------------------- @@ -7378,20 +7378,20 @@ CPU UTILIZATION: 21.531 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 621 assigned | 627 processed | 77 I stole | 71 stolen from me -Node 1 (Phys 1): 672 assigned | 641 processed | 49 I stole | 80 stolen from me -Node 2 (Phys 2): 666 assigned | 641 processed | 55 I stole | 80 stolen from me -Node 3 (Phys 3): 603 assigned | 653 processed | 95 I stole | 45 stolen from me +Node 0 (Phys 0): 605 assigned | 641 processed | 104 I stole | 68 stolen from me +Node 1 (Phys 1): 646 assigned | 637 processed | 78 I stole | 87 stolen from me +Node 2 (Phys 2): 676 assigned | 627 processed | 62 I stole | 111 stolen from me +Node 3 (Phys 3): 635 assigned | 657 processed | 95 I stole | 73 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 276 chunks (10.8%) +Total Cross-Socket Traffic: 339 chunks (13.2%) ================================================================= -3493 -real 0m0.375s -user 0m7.335s -sys 0m0.615s +3491 +real 0m0.366s +user 0m7.435s +sys 0m0.589s -CPU UTILIZATION: 21.200 / 28 +CPU UTILIZATION: 21.923 / 28 ----------------------------------------- @@ -7401,18 +7401,18 @@ CPU UTILIZATION: 21.200 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.463s -user 0m8.463s -sys 0m1.587s +real 0m0.451s +user 0m8.491s +sys 0m1.593s -CPU UTILIZATION: 21.706 / 28 +CPU UTILIZATION: 22.359 / 28 ----------------------------------------- @@ -7429,12 +7429,12 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2169118 -real 0m0.456s -user 0m8.503s -sys 0m1.615s +2168851 +real 0m0.461s +user 0m8.486s +sys 0m1.685s -CPU UTILIZATION: 22.188 / 28 +CPU UTILIZATION: 22.062 / 28 ----------------------------------------- @@ -7443,19 +7443,19 @@ CPU UTILIZATION: 22.188 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 660 assigned | 665 processed | 65 I stole | 60 stolen from me -Node 1 (Phys 1): 599 assigned | 586 processed | 55 I stole | 68 stolen from me -Node 2 (Phys 2): 657 assigned | 664 processed | 67 I stole | 60 stolen from me -Node 3 (Phys 3): 646 assigned | 647 processed | 59 I stole | 58 stolen from me +Node 0 (Phys 0): 618 assigned | 611 processed | 52 I stole | 59 stolen from me +Node 1 (Phys 1): 647 assigned | 643 processed | 49 I stole | 53 stolen from me +Node 2 (Phys 2): 651 assigned | 673 processed | 59 I stole | 37 stolen from me +Node 3 (Phys 3): 646 assigned | 635 processed | 44 I stole | 55 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 246 chunks (9.6%) +Total Cross-Socket Traffic: 204 chunks (8.0%) ================================================================= -real 0m0.449s -user 0m8.254s -sys 0m1.573s +real 0m0.443s +user 0m8.310s +sys 0m1.632s -CPU UTILIZATION: 21.886 / 28 +CPU UTILIZATION: 22.442 / 28 ----------------------------------------- @@ -7464,20 +7464,20 @@ CPU UTILIZATION: 21.886 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 662 assigned | 647 processed | 37 I stole | 52 stolen from me -Node 1 (Phys 1): 604 assigned | 609 processed | 51 I stole | 46 stolen from me -Node 2 (Phys 2): 646 assigned | 649 processed | 36 I stole | 33 stolen from me -Node 3 (Phys 3): 650 assigned | 657 processed | 39 I stole | 32 stolen from me +Node 0 (Phys 0): 658 assigned | 649 processed | 44 I stole | 53 stolen from me +Node 1 (Phys 1): 646 assigned | 670 processed | 61 I stole | 37 stolen from me +Node 2 (Phys 2): 635 assigned | 629 processed | 39 I stole | 45 stolen from me +Node 3 (Phys 3): 623 assigned | 614 processed | 43 I stole | 52 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 163 chunks (6.4%) +Total Cross-Socket Traffic: 187 chunks (7.3%) ================================================================= -2169118 -real 0m0.443s -user 0m8.348s -sys 0m1.670s +2168851 +real 0m0.441s +user 0m8.339s +sys 0m1.724s -CPU UTILIZATION: 22.613 / 28 +CPU UTILIZATION: 22.818 / 28 ----------------------------------------- @@ -7494,11 +7494,11 @@ Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.394s -user 0m7.162s -sys 0m0.499s +real 0m0.404s +user 0m7.283s +sys 0m0.480s -CPU UTILIZATION: 19.444 / 28 +CPU UTILIZATION: 19.215 / 28 ----------------------------------------- @@ -7509,18 +7509,18 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.403s -user 0m7.269s -sys 0m0.492s +real 0m0.398s +user 0m7.247s +sys 0m0.499s -CPU UTILIZATION: 19.258 / 28 +CPU UTILIZATION: 19.462 / 28 ----------------------------------------- @@ -7529,19 +7529,19 @@ CPU UTILIZATION: 19.258 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 639 assigned | 649 processed | 89 I stole | 79 stolen from me -Node 1 (Phys 1): 616 assigned | 603 processed | 85 I stole | 98 stolen from me -Node 2 (Phys 2): 644 assigned | 658 processed | 102 I stole | 88 stolen from me -Node 3 (Phys 3): 663 assigned | 652 processed | 73 I stole | 84 stolen from me +Node 0 (Phys 0): 671 assigned | 639 processed | 65 I stole | 97 stolen from me +Node 1 (Phys 1): 631 assigned | 666 processed | 92 I stole | 57 stolen from me +Node 2 (Phys 2): 638 assigned | 654 processed | 81 I stole | 65 stolen from me +Node 3 (Phys 3): 622 assigned | 603 processed | 62 I stole | 81 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 349 chunks (13.6%) +Total Cross-Socket Traffic: 300 chunks (11.7%) ================================================================= -real 0m0.359s -user 0m6.906s -sys 0m0.414s +real 0m0.356s +user 0m6.998s +sys 0m0.403s -CPU UTILIZATION: 20.389 / 28 +CPU UTILIZATION: 20.789 / 28 ----------------------------------------- @@ -7550,20 +7550,20 @@ CPU UTILIZATION: 20.389 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 675 assigned | 676 processed | 69 I stole | 68 stolen from me -Node 1 (Phys 1): 652 assigned | 653 processed | 77 I stole | 76 stolen from me -Node 2 (Phys 2): 604 assigned | 601 processed | 67 I stole | 70 stolen from me -Node 3 (Phys 3): 631 assigned | 632 processed | 64 I stole | 63 stolen from me +Node 0 (Phys 0): 696 assigned | 681 processed | 74 I stole | 89 stolen from me +Node 1 (Phys 1): 645 assigned | 656 processed | 80 I stole | 69 stolen from me +Node 2 (Phys 2): 578 assigned | 604 processed | 80 I stole | 54 stolen from me +Node 3 (Phys 3): 643 assigned | 621 processed | 60 I stole | 82 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 277 chunks (10.8%) +Total Cross-Socket Traffic: 294 chunks (11.5%) ================================================================= 0 -real 0m0.349s -user 0m6.861s -sys 0m0.415s +real 0m0.355s +user 0m6.892s +sys 0m0.446s -CPU UTILIZATION: 20.848 / 28 +CPU UTILIZATION: 20.670 / 28 ----------------------------------------- @@ -7572,19 +7572,19 @@ CPU UTILIZATION: 20.848 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.422s -user 0m7.519s -sys 0m0.627s +real 0m0.429s +user 0m7.560s +sys 0m0.633s -CPU UTILIZATION: 19.303 / 28 +CPU UTILIZATION: 19.097 / 28 ----------------------------------------- @@ -7594,19 +7594,19 @@ CPU UTILIZATION: 19.303 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1478 -real 0m0.416s -user 0m7.589s -sys 0m0.676s +real 0m0.430s +user 0m7.655s +sys 0m0.661s -CPU UTILIZATION: 19.867 / 28 +CPU UTILIZATION: 19.339 / 28 ----------------------------------------- @@ -7615,19 +7615,19 @@ CPU UTILIZATION: 19.867 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 616 assigned | 626 processed | 61 I stole | 51 stolen from me -Node 1 (Phys 1): 641 assigned | 649 processed | 51 I stole | 43 stolen from me -Node 2 (Phys 2): 649 assigned | 642 processed | 47 I stole | 54 stolen from me -Node 3 (Phys 3): 656 assigned | 645 processed | 54 I stole | 65 stolen from me +Node 0 (Phys 0): 674 assigned | 663 processed | 54 I stole | 65 stolen from me +Node 1 (Phys 1): 645 assigned | 662 processed | 71 I stole | 54 stolen from me +Node 2 (Phys 2): 627 assigned | 612 processed | 63 I stole | 78 stolen from me +Node 3 (Phys 3): 616 assigned | 625 processed | 61 I stole | 52 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 213 chunks (8.3%) +Total Cross-Socket Traffic: 249 chunks (9.7%) ================================================================= -real 0m0.374s -user 0m7.351s -sys 0m0.553s +real 0m0.372s +user 0m7.412s +sys 0m0.559s -CPU UTILIZATION: 21.133 / 28 +CPU UTILIZATION: 21.427 / 28 ----------------------------------------- @@ -7636,20 +7636,20 @@ CPU UTILIZATION: 21.133 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 679 assigned | 653 processed | 56 I stole | 82 stolen from me -Node 1 (Phys 1): 645 assigned | 640 processed | 67 I stole | 72 stolen from me -Node 2 (Phys 2): 601 assigned | 633 processed | 91 I stole | 59 stolen from me -Node 3 (Phys 3): 637 assigned | 636 processed | 70 I stole | 71 stolen from me +Node 0 (Phys 0): 622 assigned | 625 processed | 65 I stole | 62 stolen from me +Node 1 (Phys 1): 647 assigned | 652 processed | 56 I stole | 51 stolen from me +Node 2 (Phys 2): 664 assigned | 645 processed | 41 I stole | 60 stolen from me +Node 3 (Phys 3): 629 assigned | 640 processed | 45 I stole | 34 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 284 chunks (11.1%) +Total Cross-Socket Traffic: 207 chunks (8.1%) ================================================================= -3460 -real 0m0.369s -user 0m7.286s -sys 0m0.581s +3458 +real 0m0.364s +user 0m7.352s +sys 0m0.598s -CPU UTILIZATION: 21.319 / 28 +CPU UTILIZATION: 21.840 / 28 ----------------------------------------- @@ -7660,17 +7660,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.522s -user 0m8.569s -sys 0m1.620s +real 0m0.496s +user 0m8.613s +sys 0m1.671s -CPU UTILIZATION: 19.519 / 28 +CPU UTILIZATION: 20.733 / 28 ----------------------------------------- @@ -7679,20 +7679,20 @@ CPU UTILIZATION: 19.519 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2169118 -real 0m0.501s -user 0m8.584s -sys 0m1.699s +2168851 +real 0m0.505s +user 0m8.484s +sys 0m1.714s -CPU UTILIZATION: 20.524 / 28 +CPU UTILIZATION: 20.194 / 28 ----------------------------------------- @@ -7701,19 +7701,19 @@ CPU UTILIZATION: 20.524 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 653 assigned | 643 processed | 59 I stole | 69 stolen from me -Node 1 (Phys 1): 636 assigned | 619 processed | 47 I stole | 64 stolen from me -Node 2 (Phys 2): 625 assigned | 649 processed | 70 I stole | 46 stolen from me -Node 3 (Phys 3): 648 assigned | 651 processed | 50 I stole | 47 stolen from me +Node 0 (Phys 0): 630 assigned | 646 processed | 42 I stole | 26 stolen from me +Node 1 (Phys 1): 656 assigned | 640 processed | 22 I stole | 38 stolen from me +Node 2 (Phys 2): 652 assigned | 648 processed | 32 I stole | 36 stolen from me +Node 3 (Phys 3): 624 assigned | 628 processed | 39 I stole | 35 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 226 chunks (8.8%) +Total Cross-Socket Traffic: 135 chunks (5.3%) ================================================================= -real 0m0.449s -user 0m8.494s -sys 0m1.669s +real 0m0.437s +user 0m8.317s +sys 0m1.633s -CPU UTILIZATION: 22.634 / 28 +CPU UTILIZATION: 22.768 / 28 ----------------------------------------- @@ -7722,20 +7722,20 @@ CPU UTILIZATION: 22.634 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 617 assigned | 611 processed | 49 I stole | 55 stolen from me -Node 1 (Phys 1): 688 assigned | 679 processed | 39 I stole | 48 stolen from me -Node 2 (Phys 2): 645 assigned | 674 processed | 64 I stole | 35 stolen from me -Node 3 (Phys 3): 612 assigned | 598 processed | 49 I stole | 63 stolen from me +Node 0 (Phys 0): 635 assigned | 643 processed | 58 I stole | 50 stolen from me +Node 1 (Phys 1): 659 assigned | 664 processed | 51 I stole | 46 stolen from me +Node 2 (Phys 2): 635 assigned | 617 processed | 38 I stole | 56 stolen from me +Node 3 (Phys 3): 633 assigned | 638 processed | 46 I stole | 41 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 201 chunks (7.8%) +Total Cross-Socket Traffic: 193 chunks (7.5%) ================================================================= -2169118 -real 0m0.444s -user 0m8.216s -sys 0m1.653s +2168851 +real 0m0.439s +user 0m8.268s +sys 0m1.739s -CPU UTILIZATION: 22.227 / 28 +CPU UTILIZATION: 22.794 / 28 ----------------------------------------- @@ -7744,19 +7744,19 @@ CPU UTILIZATION: 22.227 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.141s -user 0m0.173s -sys 0m0.281s +real 0m0.138s +user 0m0.224s +sys 0m0.300s -CPU UTILIZATION: 3.219 / 28 +CPU UTILIZATION: 3.797 / 28 ----------------------------------------- @@ -7766,19 +7766,19 @@ CPU UTILIZATION: 3.219 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.144s -user 0m0.188s -sys 0m0.270s +real 0m0.139s +user 0m0.157s +sys 0m0.296s -CPU UTILIZATION: 3.180 / 28 +CPU UTILIZATION: 3.258 / 28 ----------------------------------------- @@ -7787,19 +7787,19 @@ CPU UTILIZATION: 3.180 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 662 assigned | 686 processed | 24 I stole | 0 stolen from me -Node 1 (Phys 1): 638 assigned | 624 processed | 0 I stole | 14 stolen from me -Node 2 (Phys 2): 619 assigned | 612 processed | 0 I stole | 7 stolen from me -Node 3 (Phys 3): 643 assigned | 640 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 657 assigned | 671 processed | 14 I stole | 0 stolen from me +Node 1 (Phys 1): 652 assigned | 653 processed | 4 I stole | 3 stolen from me +Node 2 (Phys 2): 634 assigned | 624 processed | 0 I stole | 10 stolen from me +Node 3 (Phys 3): 619 assigned | 614 processed | 0 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 24 chunks (0.9%) +Total Cross-Socket Traffic: 18 chunks (0.7%) ================================================================= -real 0m0.166s -user 0m0.452s -sys 0m0.604s +real 0m0.168s +user 0m0.491s +sys 0m0.621s -CPU UTILIZATION: 6.361 / 28 +CPU UTILIZATION: 6.619 / 28 ----------------------------------------- @@ -7808,20 +7808,20 @@ CPU UTILIZATION: 6.361 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 657 assigned | 666 processed | 9 I stole | 0 stolen from me -Node 1 (Phys 1): 637 assigned | 631 processed | 0 I stole | 6 stolen from me -Node 2 (Phys 2): 647 assigned | 646 processed | 1 I stole | 2 stolen from me -Node 3 (Phys 3): 621 assigned | 619 processed | 0 I stole | 2 stolen from me +Node 0 (Phys 0): 690 assigned | 697 processed | 7 I stole | 0 stolen from me +Node 1 (Phys 1): 645 assigned | 645 processed | 4 I stole | 4 stolen from me +Node 2 (Phys 2): 626 assigned | 623 processed | 1 I stole | 4 stolen from me +Node 3 (Phys 3): 601 assigned | 597 processed | 0 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 10 chunks (0.4%) +Total Cross-Socket Traffic: 12 chunks (0.5%) ================================================================= 0 -real 0m0.161s -user 0m0.514s -sys 0m0.582s +real 0m0.163s +user 0m0.495s +sys 0m0.569s -CPU UTILIZATION: 6.807 / 28 +CPU UTILIZATION: 6.527 / 28 ----------------------------------------- @@ -7830,19 +7830,19 @@ CPU UTILIZATION: 6.807 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.156s -user 0m0.670s -sys 0m0.928s +real 0m0.157s +user 0m0.711s +sys 0m0.912s -CPU UTILIZATION: 10.243 / 28 +CPU UTILIZATION: 10.337 / 28 ----------------------------------------- @@ -7851,20 +7851,20 @@ CPU UTILIZATION: 10.243 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 24 assigned | 25 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -2113379 -real 0m0.181s -user 0m0.700s -sys 0m0.941s +2113621 +real 0m0.179s +user 0m0.693s +sys 0m0.979s -CPU UTILIZATION: 9.066 / 28 +CPU UTILIZATION: 9.340 / 28 ----------------------------------------- @@ -7873,19 +7873,19 @@ CPU UTILIZATION: 9.066 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 652 assigned | 656 processed | 6 I stole | 2 stolen from me -Node 1 (Phys 1): 631 assigned | 628 processed | 1 I stole | 4 stolen from me -Node 2 (Phys 2): 638 assigned | 637 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 641 assigned | 641 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 647 assigned | 652 processed | 7 I stole | 2 stolen from me +Node 1 (Phys 1): 655 assigned | 652 processed | 0 I stole | 3 stolen from me +Node 2 (Phys 2): 637 assigned | 637 processed | 4 I stole | 4 stolen from me +Node 3 (Phys 3): 623 assigned | 621 processed | 1 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 11 chunks (0.4%) +Total Cross-Socket Traffic: 12 chunks (0.5%) ================================================================= -real 0m0.225s -user 0m1.568s -sys 0m1.580s +real 0m0.226s +user 0m1.613s +sys 0m1.551s -CPU UTILIZATION: 13.991 / 28 +CPU UTILIZATION: 14.000 / 28 ----------------------------------------- @@ -7894,20 +7894,20 @@ CPU UTILIZATION: 13.991 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 646 assigned | 649 processed | 7 I stole | 4 stolen from me -Node 1 (Phys 1): 648 assigned | 653 processed | 7 I stole | 2 stolen from me -Node 2 (Phys 2): 639 assigned | 633 processed | 0 I stole | 6 stolen from me -Node 3 (Phys 3): 629 assigned | 627 processed | 3 I stole | 5 stolen from me +Node 0 (Phys 0): 650 assigned | 652 processed | 5 I stole | 3 stolen from me +Node 1 (Phys 1): 652 assigned | 654 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 637 assigned | 634 processed | 2 I stole | 5 stolen from me +Node 3 (Phys 3): 623 assigned | 622 processed | 2 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (0.7%) +Total Cross-Socket Traffic: 11 chunks (0.4%) ================================================================= -2113379 +2113621 real 0m0.226s -user 0m1.574s -sys 0m1.640s +user 0m1.583s +sys 0m1.707s -CPU UTILIZATION: 14.221 / 28 +CPU UTILIZATION: 14.557 / 28 ----------------------------------------- @@ -7916,19 +7916,19 @@ CPU UTILIZATION: 14.221 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 25 processed | 2 I stole | 0 stolen from me Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 18 assigned | 16 processed | 0 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= -real 0m0.163s -user 0m0.676s -sys 0m0.854s +real 0m0.158s +user 0m0.697s +sys 0m0.841s -CPU UTILIZATION: 9.386 / 28 +CPU UTILIZATION: 9.734 / 28 ----------------------------------------- @@ -7937,20 +7937,20 @@ CPU UTILIZATION: 9.386 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 24 assigned | 26 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= -2113379 -real 0m0.181s -user 0m0.695s -sys 0m0.935s +2113621 +real 0m0.175s +user 0m0.707s +sys 0m0.933s -CPU UTILIZATION: 9.005 / 28 +CPU UTILIZATION: 9.371 / 28 ----------------------------------------- @@ -7959,19 +7959,19 @@ CPU UTILIZATION: 9.005 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 665 assigned | 667 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 643 assigned | 640 processed | 1 I stole | 4 stolen from me -Node 2 (Phys 2): 635 assigned | 638 processed | 4 I stole | 1 stolen from me -Node 3 (Phys 3): 619 assigned | 617 processed | 2 I stole | 4 stolen from me +Node 0 (Phys 0): 633 assigned | 639 processed | 8 I stole | 2 stolen from me +Node 1 (Phys 1): 648 assigned | 648 processed | 3 I stole | 3 stolen from me +Node 2 (Phys 2): 651 assigned | 650 processed | 4 I stole | 5 stolen from me +Node 3 (Phys 3): 630 assigned | 625 processed | 0 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.4%) +Total Cross-Socket Traffic: 15 chunks (0.6%) ================================================================= -real 0m0.225s -user 0m1.552s -sys 0m1.506s +real 0m0.220s +user 0m1.562s +sys 0m1.516s -CPU UTILIZATION: 13.591 / 28 +CPU UTILIZATION: 13.990 / 28 ----------------------------------------- @@ -7980,20 +7980,20 @@ CPU UTILIZATION: 13.591 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 621 assigned | 628 processed | 10 I stole | 3 stolen from me -Node 1 (Phys 1): 647 assigned | 648 processed | 4 I stole | 3 stolen from me -Node 2 (Phys 2): 649 assigned | 636 processed | 1 I stole | 14 stolen from me -Node 3 (Phys 3): 645 assigned | 650 processed | 7 I stole | 2 stolen from me +Node 0 (Phys 0): 629 assigned | 636 processed | 9 I stole | 2 stolen from me +Node 1 (Phys 1): 634 assigned | 637 processed | 6 I stole | 3 stolen from me +Node 2 (Phys 2): 653 assigned | 649 processed | 3 I stole | 7 stolen from me +Node 3 (Phys 3): 646 assigned | 640 processed | 1 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 22 chunks (0.9%) +Total Cross-Socket Traffic: 19 chunks (0.7%) ================================================================= -2113379 -real 0m0.223s -user 0m1.603s -sys 0m1.550s +2113621 +real 0m0.222s +user 0m1.536s +sys 0m1.635s -CPU UTILIZATION: 14.139 / 28 +CPU UTILIZATION: 14.283 / 28 ----------------------------------------- @@ -8003,18 +8003,18 @@ CPU UTILIZATION: 14.139 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.141s -user 0m0.064s -sys 0m0.190s +real 0m0.137s +user 0m0.058s +sys 0m0.194s -CPU UTILIZATION: 1.801 / 28 +CPU UTILIZATION: 1.839 / 28 ----------------------------------------- @@ -8032,11 +8032,11 @@ Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 0 -real 0m0.146s -user 0m0.069s -sys 0m0.192s +real 0m0.143s +user 0m0.055s +sys 0m0.203s -CPU UTILIZATION: 1.787 / 28 +CPU UTILIZATION: 1.804 / 28 ----------------------------------------- @@ -8045,19 +8045,19 @@ CPU UTILIZATION: 1.787 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 644 assigned | 652 processed | 8 I stole | 0 stolen from me -Node 1 (Phys 1): 644 assigned | 639 processed | 0 I stole | 5 stolen from me -Node 2 (Phys 2): 638 assigned | 638 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 636 assigned | 633 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 651 assigned | 668 processed | 17 I stole | 0 stolen from me +Node 1 (Phys 1): 639 assigned | 630 processed | 1 I stole | 10 stolen from me +Node 2 (Phys 2): 638 assigned | 637 processed | 2 I stole | 3 stolen from me +Node 3 (Phys 3): 634 assigned | 627 processed | 0 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.4%) +Total Cross-Socket Traffic: 20 chunks (0.8%) ================================================================= -real 0m0.161s -user 0m0.376s -sys 0m0.363s +real 0m0.164s +user 0m0.368s +sys 0m0.380s -CPU UTILIZATION: 4.590 / 28 +CPU UTILIZATION: 4.560 / 28 ----------------------------------------- @@ -8066,20 +8066,20 @@ CPU UTILIZATION: 4.590 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 645 assigned | 659 processed | 14 I stole | 0 stolen from me -Node 1 (Phys 1): 643 assigned | 639 processed | 1 I stole | 5 stolen from me -Node 2 (Phys 2): 637 assigned | 632 processed | 0 I stole | 5 stolen from me -Node 3 (Phys 3): 637 assigned | 632 processed | 0 I stole | 5 stolen from me +Node 0 (Phys 0): 644 assigned | 643 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 640 assigned | 635 processed | 0 I stole | 5 stolen from me +Node 2 (Phys 2): 644 assigned | 654 processed | 10 I stole | 0 stolen from me +Node 3 (Phys 3): 634 assigned | 630 processed | 0 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 15 chunks (0.6%) +Total Cross-Socket Traffic: 10 chunks (0.4%) ================================================================= 0 -real 0m0.149s -user 0m0.314s -sys 0m0.388s +real 0m0.154s +user 0m0.354s +sys 0m0.357s -CPU UTILIZATION: 4.711 / 28 +CPU UTILIZATION: 4.616 / 28 ----------------------------------------- @@ -8096,11 +8096,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.134s -user 0m0.134s -sys 0m0.309s +real 0m0.139s +user 0m0.152s +sys 0m0.317s -CPU UTILIZATION: 3.305 / 28 +CPU UTILIZATION: 3.374 / 28 ----------------------------------------- @@ -8109,20 +8109,20 @@ CPU UTILIZATION: 3.305 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m0.138s +2113621 +real 0m0.140s user 0m0.147s -sys 0m0.368s +sys 0m0.377s -CPU UTILIZATION: 3.731 / 28 +CPU UTILIZATION: 3.742 / 28 ----------------------------------------- @@ -8131,19 +8131,19 @@ CPU UTILIZATION: 3.731 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 635 assigned | 639 processed | 5 I stole | 1 stolen from me -Node 1 (Phys 1): 643 assigned | 645 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 643 assigned | 641 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 641 assigned | 637 processed | 0 I stole | 4 stolen from me +Node 0 (Phys 0): 640 assigned | 643 processed | 3 I stole | 0 stolen from me +Node 1 (Phys 1): 646 assigned | 645 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 639 assigned | 638 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 637 assigned | 636 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 8 chunks (0.3%) +Total Cross-Socket Traffic: 4 chunks (0.2%) ================================================================= -real 0m0.200s -user 0m0.930s -sys 0m0.907s +real 0m0.203s +user 0m0.939s +sys 0m0.893s -CPU UTILIZATION: 9.185 / 28 +CPU UTILIZATION: 9.024 / 28 ----------------------------------------- @@ -8152,20 +8152,20 @@ CPU UTILIZATION: 9.185 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 647 assigned | 649 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 653 assigned | 651 processed | 1 I stole | 3 stolen from me -Node 2 (Phys 2): 629 assigned | 628 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 633 assigned | 634 processed | 2 I stole | 1 stolen from me +Node 0 (Phys 0): 640 assigned | 641 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 634 assigned | 636 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 642 assigned | 640 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 646 assigned | 645 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 8 chunks (0.3%) +Total Cross-Socket Traffic: 3 chunks (0.1%) ================================================================= -2113379 +2113621 real 0m0.202s -user 0m0.920s -sys 0m0.988s +user 0m0.945s +sys 0m0.990s -CPU UTILIZATION: 9.445 / 28 +CPU UTILIZATION: 9.579 / 28 ----------------------------------------- @@ -8174,19 +8174,19 @@ CPU UTILIZATION: 9.445 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.137s -user 0m0.142s -sys 0m0.317s +real 0m0.139s +user 0m0.135s +sys 0m0.324s -CPU UTILIZATION: 3.350 / 28 +CPU UTILIZATION: 3.302 / 28 ----------------------------------------- @@ -8203,12 +8203,12 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m0.140s -user 0m0.157s -sys 0m0.383s +2113621 +real 0m0.139s +user 0m0.153s +sys 0m0.374s -CPU UTILIZATION: 3.857 / 28 +CPU UTILIZATION: 3.791 / 28 ----------------------------------------- @@ -8217,19 +8217,19 @@ CPU UTILIZATION: 3.857 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 652 assigned | 652 processed | 5 I stole | 5 stolen from me -Node 1 (Phys 1): 638 assigned | 640 processed | 5 I stole | 3 stolen from me -Node 2 (Phys 2): 632 assigned | 632 processed | 3 I stole | 3 stolen from me -Node 3 (Phys 3): 640 assigned | 638 processed | 3 I stole | 5 stolen from me +Node 0 (Phys 0): 648 assigned | 648 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 642 assigned | 641 processed | 4 I stole | 5 stolen from me +Node 2 (Phys 2): 635 assigned | 636 processed | 2 I stole | 1 stolen from me +Node 3 (Phys 3): 637 assigned | 637 processed | 2 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 16 chunks (0.6%) +Total Cross-Socket Traffic: 9 chunks (0.4%) ================================================================= -real 0m0.198s -user 0m0.902s -sys 0m0.880s +real 0m0.195s +user 0m0.929s +sys 0m0.869s -CPU UTILIZATION: 9.000 / 28 +CPU UTILIZATION: 9.220 / 28 ----------------------------------------- @@ -8238,20 +8238,20 @@ CPU UTILIZATION: 9.000 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 640 assigned | 642 processed | 5 I stole | 3 stolen from me -Node 1 (Phys 1): 644 assigned | 642 processed | 5 I stole | 7 stolen from me -Node 2 (Phys 2): 634 assigned | 634 processed | 5 I stole | 5 stolen from me -Node 3 (Phys 3): 644 assigned | 644 processed | 4 I stole | 4 stolen from me +Node 0 (Phys 0): 648 assigned | 646 processed | 2 I stole | 4 stolen from me +Node 1 (Phys 1): 637 assigned | 638 processed | 7 I stole | 6 stolen from me +Node 2 (Phys 2): 644 assigned | 643 processed | 4 I stole | 5 stolen from me +Node 3 (Phys 3): 633 assigned | 635 processed | 4 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 19 chunks (0.7%) +Total Cross-Socket Traffic: 17 chunks (0.7%) ================================================================= -2113379 -real 0m0.199s -user 0m0.901s -sys 0m0.972s +2113621 +real 0m0.198s +user 0m0.918s +sys 0m0.976s -CPU UTILIZATION: 9.412 / 28 +CPU UTILIZATION: 9.565 / 28 ----------------------------------------- @@ -8260,19 +8260,19 @@ CPU UTILIZATION: 9.412 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.221s -user 0m2.541s -sys 0m1.224s +real 0m0.224s +user 0m2.793s +sys 0m1.111s -CPU UTILIZATION: 17.036 / 28 +CPU UTILIZATION: 17.428 / 28 ----------------------------------------- @@ -8282,19 +8282,19 @@ CPU UTILIZATION: 17.036 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.220s -user 0m2.602s -sys 0m1.082s +real 0m0.222s +user 0m2.781s +sys 0m1.150s -CPU UTILIZATION: 16.745 / 28 +CPU UTILIZATION: 17.707 / 28 ----------------------------------------- @@ -8303,19 +8303,19 @@ CPU UTILIZATION: 16.745 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 622 assigned | 646 processed | 64 I stole | 40 stolen from me -Node 1 (Phys 1): 641 assigned | 626 processed | 43 I stole | 58 stolen from me -Node 2 (Phys 2): 642 assigned | 623 processed | 29 I stole | 48 stolen from me -Node 3 (Phys 3): 657 assigned | 667 processed | 45 I stole | 35 stolen from me +Node 0 (Phys 0): 610 assigned | 605 processed | 27 I stole | 32 stolen from me +Node 1 (Phys 1): 674 assigned | 685 processed | 34 I stole | 23 stolen from me +Node 2 (Phys 2): 623 assigned | 606 processed | 15 I stole | 32 stolen from me +Node 3 (Phys 3): 655 assigned | 666 processed | 27 I stole | 16 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 181 chunks (7.1%) +Total Cross-Socket Traffic: 103 chunks (4.0%) ================================================================= -real 0m0.246s -user 0m2.671s -sys 0m1.390s +real 0m0.239s +user 0m2.762s +sys 0m1.263s -CPU UTILIZATION: 16.508 / 28 +CPU UTILIZATION: 16.841 / 28 ----------------------------------------- @@ -8324,20 +8324,20 @@ CPU UTILIZATION: 16.508 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 660 assigned | 651 processed | 25 I stole | 34 stolen from me -Node 1 (Phys 1): 661 assigned | 667 processed | 31 I stole | 25 stolen from me -Node 2 (Phys 2): 601 assigned | 596 processed | 29 I stole | 34 stolen from me -Node 3 (Phys 3): 640 assigned | 648 processed | 34 I stole | 26 stolen from me +Node 0 (Phys 0): 681 assigned | 656 processed | 27 I stole | 52 stolen from me +Node 1 (Phys 1): 639 assigned | 625 processed | 30 I stole | 44 stolen from me +Node 2 (Phys 2): 596 assigned | 623 processed | 56 I stole | 29 stolen from me +Node 3 (Phys 3): 646 assigned | 658 processed | 40 I stole | 28 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 119 chunks (4.6%) +Total Cross-Socket Traffic: 153 chunks (6.0%) ================================================================= 0 -real 0m0.249s -user 0m2.704s -sys 0m1.361s +real 0m0.254s +user 0m2.766s +sys 0m1.407s -CPU UTILIZATION: 16.325 / 28 +CPU UTILIZATION: 16.429 / 28 ----------------------------------------- @@ -8354,11 +8354,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.151s -user 0m14.463s -sys 0m11.968s +real 0m1.163s +user 0m14.678s +sys 0m12.030s -CPU UTILIZATION: 22.963 / 28 +CPU UTILIZATION: 22.964 / 28 ----------------------------------------- @@ -8375,12 +8375,12 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m1.158s -user 0m14.605s -sys 0m12.082s +2113621 +real 0m1.171s +user 0m14.601s +sys 0m12.328s -CPU UTILIZATION: 23.045 / 28 +CPU UTILIZATION: 22.996 / 28 ----------------------------------------- @@ -8389,19 +8389,19 @@ CPU UTILIZATION: 23.045 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 644 assigned | 645 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 642 assigned | 640 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 639 assigned | 640 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 637 assigned | 637 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 643 assigned | 644 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 640 assigned | 640 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 641 assigned | 640 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 638 assigned | 638 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.141s -user 0m14.470s -sys 0m12.170s +real 0m1.163s +user 0m14.552s +sys 0m12.493s -CPU UTILIZATION: 23.347 / 28 +CPU UTILIZATION: 23.254 / 28 ----------------------------------------- @@ -8410,20 +8410,20 @@ CPU UTILIZATION: 23.347 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 643 assigned | 644 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 642 assigned | 642 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 639 assigned | 638 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 638 assigned | 638 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 647 assigned | 647 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 640 assigned | 640 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 639 assigned | 639 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 636 assigned | 636 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -2113379 -real 0m1.162s -user 0m14.448s -sys 0m12.404s +2113621 +real 0m1.169s +user 0m14.682s +sys 0m12.508s -CPU UTILIZATION: 23.108 / 28 +CPU UTILIZATION: 23.259 / 28 ----------------------------------------- @@ -8440,11 +8440,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.129s -user 0m14.391s -sys 0m11.574s +real 0m1.138s +user 0m14.592s +sys 0m11.701s -CPU UTILIZATION: 22.998 / 28 +CPU UTILIZATION: 23.104 / 28 ----------------------------------------- @@ -8461,12 +8461,12 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m1.141s -user 0m14.451s -sys 0m11.800s +2113621 +real 0m1.154s +user 0m14.544s +sys 0m11.957s -CPU UTILIZATION: 23.007 / 28 +CPU UTILIZATION: 22.964 / 28 ----------------------------------------- @@ -8475,19 +8475,19 @@ CPU UTILIZATION: 23.007 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 645 assigned | 644 processed | 1 I stole | 2 stolen from me -Node 1 (Phys 1): 640 assigned | 639 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 642 assigned | 644 processed | 2 I stole | 0 stolen from me -Node 3 (Phys 3): 635 assigned | 635 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 641 assigned | 643 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 641 assigned | 641 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 639 assigned | 638 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 641 assigned | 640 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.2%) +Total Cross-Socket Traffic: 3 chunks (0.1%) ================================================================= -real 0m1.139s -user 0m14.472s -sys 0m11.895s +real 0m1.144s +user 0m14.600s +sys 0m11.971s -CPU UTILIZATION: 23.149 / 28 +CPU UTILIZATION: 23.226 / 28 ----------------------------------------- @@ -8496,20 +8496,20 @@ CPU UTILIZATION: 23.149 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 641 assigned | 641 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 641 assigned | 642 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 642 assigned | 641 processed | 1 I stole | 2 stolen from me -Node 3 (Phys 3): 638 assigned | 638 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 643 assigned | 643 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 641 assigned | 641 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 638 assigned | 638 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 640 assigned | 640 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -2113379 -real 0m1.147s -user 0m14.496s -sys 0m12.046s +2113621 +real 0m1.155s +user 0m14.616s +sys 0m12.171s -CPU UTILIZATION: 23.140 / 28 +CPU UTILIZATION: 23.192 / 28 ----------------------------------------- @@ -8530,15 +8530,15 @@ LINE COUNT: 100000000 lines NAME: f3 -SIZE: 167782912 bytes -LINE COUNT: 2113379 lines +SIZE: 167808321 bytes +LINE COUNT: 2113621 lines -total sys = 4358959 ms +total sys = 4385244 ms -total user = 7337672 ms +total user = 7381081 ms -total real = 480177 ms +total real = 482751 ms -OVERALL CPU UTILIZATION: 24.358 / 28 +OVERALL CPU UTILIZATION: 24.373 / 28 diff --git a/BENCHMARKS/benchmark.out b/BENCHMARKS/benchmark.out deleted file mode 100644 index 4f79822c..00000000 --- a/BENCHMARKS/benchmark.out +++ /dev/null @@ -1,8544 +0,0 @@ - -(1): time { frun -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.143s -user 0m6.340s -sys 0m20.616s - -CPU UTILIZATION: 23.583 / 28 - ------------------------------------------ - -(2): time { frun -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.135s -user 0m6.503s -sys 0m20.667s - -CPU UTILIZATION: 23.938 / 28 - ------------------------------------------ - -(4): time { cat f1 | frun -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 383 assigned | 382 processed | 1 I stole | 2 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 384 processed | 2 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 1 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 4 chunks (0.3%) -================================================================= - -0 -real 0m1.137s -user 0m6.473s -sys 0m20.769s - -CPU UTILIZATION: 23.959 / 28 - ------------------------------------------ - -(5): time { frun -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.204s -user 0m6.414s -sys 0m22.317s - -CPU UTILIZATION: 23.862 / 28 - ------------------------------------------ - -(6): time { frun -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.206s -user 0m6.587s -sys 0m22.398s - -CPU UTILIZATION: 24.033 / 28 - ------------------------------------------ - -(8): time { cat f1 | frun -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -25555 -real 0m1.206s -user 0m6.578s -sys 0m22.553s - -CPU UTILIZATION: 24.155 / 28 - ------------------------------------------ - -(9): time { frun -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.898s -user 0m25.420s -sys 0m21.972s - -CPU UTILIZATION: 24.969 / 28 - ------------------------------------------ - -(10): time { frun -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -real 0m1.897s -user 0m25.718s -sys 0m21.872s - -CPU UTILIZATION: 25.086 / 28 - ------------------------------------------ - -(12): time { cat f1 | frun -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 379 assigned | 380 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -100000000 -real 0m1.905s -user 0m25.550s -sys 0m22.217s - -CPU UTILIZATION: 25.074 / 28 - ------------------------------------------ - -(13): time { frun -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.659s -user 0m1.588s -sys 0m13.802s - -CPU UTILIZATION: 23.353 / 28 - ------------------------------------------ - -(14): time { frun -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 387 assigned | 385 processed | 0 I stole | 2 stolen from me -Node 1 (Phys 1): 383 assigned | 385 processed | 2 I stole | 0 stolen from me -Node 2 (Phys 2): 376 assigned | 379 processed | 4 I stole | 1 stolen from me -Node 3 (Phys 3): 381 assigned | 378 processed | 0 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.4%) -================================================================= - -real 0m0.706s -user 0m2.475s -sys 0m14.221s - -CPU UTILIZATION: 23.648 / 28 - ------------------------------------------ - -(16): time { cat f1 | frun -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 2 I stole | 3 stolen from me -Node 1 (Phys 1): 380 assigned | 379 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 380 assigned | 382 processed | 2 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 4 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 9 chunks (0.6%) -================================================================= - -0 -real 0m0.707s -user 0m2.455s -sys 0m14.192s - -CPU UTILIZATION: 23.545 / 28 - ------------------------------------------ - -(17): time { frun -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.702s -user 0m2.378s -sys 0m14.153s - -CPU UTILIZATION: 23.548 / 28 - ------------------------------------------ - -(18): time { frun -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 383 processed | 1 I stole | 3 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 380 assigned | 383 processed | 3 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.4%) -================================================================= - -real 0m0.746s -user 0m3.307s -sys 0m14.524s - -CPU UTILIZATION: 23.902 / 28 - ------------------------------------------ - -(20): time { cat f1 | frun -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 388 assigned | 385 processed | 6 I stole | 9 stolen from me -Node 1 (Phys 1): 381 assigned | 383 processed | 9 I stole | 7 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 4 I stole | 4 stolen from me -Node 3 (Phys 3): 376 assigned | 377 processed | 5 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 24 chunks (1.6%) -================================================================= - -5965 -real 0m0.751s -user 0m3.225s -sys 0m14.683s - -CPU UTILIZATION: 23.845 / 28 - ------------------------------------------ - -(21): time { frun -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.412s -user 0m21.450s -sys 0m14.437s - -CPU UTILIZATION: 25.415 / 28 - ------------------------------------------ - -(22): time { frun -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 378 assigned | 379 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -real 0m1.461s -user 0m22.252s -sys 0m14.849s - -CPU UTILIZATION: 25.394 / 28 - ------------------------------------------ - -(24): time { cat f1 | frun -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -100000000 -real 0m1.463s -user 0m22.290s -sys 0m14.905s - -CPU UTILIZATION: 25.423 / 28 - ------------------------------------------ - -(25): time { frun -k -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.135s -user 0m6.361s -sys 0m20.553s - -CPU UTILIZATION: 23.712 / 28 - ------------------------------------------ - -(26): time { frun -k -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.137s -user 0m6.387s -sys 0m20.759s - -CPU UTILIZATION: 23.875 / 28 - ------------------------------------------ - -(28): time { cat f1 | frun -k -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 384 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -0 -real 0m1.131s -user 0m6.382s -sys 0m20.744s - -CPU UTILIZATION: 23.984 / 28 - ------------------------------------------ - -(29): time { frun -k -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.204s -user 0m6.492s -sys 0m22.211s - -CPU UTILIZATION: 23.839 / 28 - ------------------------------------------ - -(30): time { frun -k -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.204s -user 0m6.666s -sys 0m22.307s - -CPU UTILIZATION: 24.063 / 28 - ------------------------------------------ - -(32): time { cat f1 | frun -k -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 384 processed | 3 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 381 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.2%) -================================================================= - -25555 -real 0m1.208s -user 0m6.785s -sys 0m22.267s - -CPU UTILIZATION: 24.049 / 28 - ------------------------------------------ - -(33): time { frun -k -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.893s -user 0m25.430s -sys 0m21.868s - -CPU UTILIZATION: 24.985 / 28 - ------------------------------------------ - -(34): time { frun -k -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -real 0m1.899s -user 0m25.370s -sys 0m22.222s - -CPU UTILIZATION: 25.061 / 28 - ------------------------------------------ - -(36): time { cat f1 | frun -k -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 382 assigned | 381 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -100000000 -real 0m1.905s -user 0m25.434s -sys 0m22.319s - -CPU UTILIZATION: 25.067 / 28 - ------------------------------------------ - -(37): time { frun -k -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.665s -user 0m1.619s -sys 0m13.835s - -CPU UTILIZATION: 23.239 / 28 - ------------------------------------------ - -(38): time { frun -k -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 389 assigned | 385 processed | 2 I stole | 6 stolen from me -Node 1 (Phys 1): 380 assigned | 383 processed | 6 I stole | 3 stolen from me -Node 2 (Phys 2): 378 assigned | 380 processed | 4 I stole | 2 stolen from me -Node 3 (Phys 3): 380 assigned | 379 processed | 3 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 15 chunks (1.0%) -================================================================= - -real 0m0.709s -user 0m2.460s -sys 0m14.254s - -CPU UTILIZATION: 23.574 / 28 - ------------------------------------------ - -(40): time { cat f1 | frun -k -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 391 assigned | 390 processed | 7 I stole | 8 stolen from me -Node 1 (Phys 1): 384 assigned | 382 processed | 5 I stole | 7 stolen from me -Node 2 (Phys 2): 377 assigned | 376 processed | 8 I stole | 9 stolen from me -Node 3 (Phys 3): 375 assigned | 379 processed | 11 I stole | 7 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 31 chunks (2.0%) -================================================================= - -0 -real 0m0.714s -user 0m2.513s -sys 0m14.201s - -CPU UTILIZATION: 23.408 / 28 - ------------------------------------------ - -(41): time { frun -k -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.701s -user 0m2.368s -sys 0m14.145s - -CPU UTILIZATION: 23.556 / 28 - ------------------------------------------ - -(42): time { frun -k -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 385 processed | 8 I stole | 4 stolen from me -Node 1 (Phys 1): 374 assigned | 378 processed | 8 I stole | 4 stolen from me -Node 2 (Phys 2): 388 assigned | 383 processed | 0 I stole | 5 stolen from me -Node 3 (Phys 3): 384 assigned | 381 processed | 3 I stole | 6 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 19 chunks (1.2%) -================================================================= - -real 0m0.748s -user 0m3.268s -sys 0m14.583s - -CPU UTILIZATION: 23.864 / 28 - ------------------------------------------ - -(44): time { cat f1 | frun -k -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 386 assigned | 384 processed | 1 I stole | 3 stolen from me -Node 1 (Phys 1): 386 assigned | 384 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 372 assigned | 375 processed | 3 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 5 chunks (0.3%) -================================================================= - -5965 -real 0m0.754s -user 0m3.248s -sys 0m14.644s - -CPU UTILIZATION: 23.729 / 28 - ------------------------------------------ - -(45): time { frun -k -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.403s -user 0m21.385s -sys 0m14.404s - -CPU UTILIZATION: 25.508 / 28 - ------------------------------------------ - -(46): time { frun -k -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.460s -user 0m22.277s -sys 0m14.838s - -CPU UTILIZATION: 25.421 / 28 - ------------------------------------------ - -(48): time { cat f1 | frun -k -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -100000000 -real 0m1.456s -user 0m22.289s -sys 0m14.878s - -CPU UTILIZATION: 25.526 / 28 - ------------------------------------------ - -(49): time { frun -u -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.103s -user 0m6.078s -sys 0m20.089s - -CPU UTILIZATION: 23.723 / 28 - ------------------------------------------ - -(50): time { frun -u -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -real 0m1.107s -user 0m6.046s -sys 0m20.402s - -CPU UTILIZATION: 23.891 / 28 - ------------------------------------------ - -(52): time { cat f1 | frun -u -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 1 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -0 -real 0m1.108s -user 0m6.209s -sys 0m20.239s - -CPU UTILIZATION: 23.870 / 28 - ------------------------------------------ - -(53): time { frun -u -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.161s -user 0m6.248s -sys 0m21.560s - -CPU UTILIZATION: 23.951 / 28 - ------------------------------------------ - -(54): time { frun -u -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 384 processed | 3 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.2%) -================================================================= - -real 0m1.164s -user 0m6.248s -sys 0m21.761s - -CPU UTILIZATION: 24.062 / 28 - ------------------------------------------ - -(56): time { cat f1 | frun -u -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -25555 -real 0m1.175s -user 0m6.298s -sys 0m21.901s - -CPU UTILIZATION: 23.999 / 28 - ------------------------------------------ - -(57): time { frun -u -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.858s -user 0m25.032s -sys 0m21.346s - -CPU UTILIZATION: 24.961 / 28 - ------------------------------------------ - -(58): time { frun -u -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -real 0m1.859s -user 0m25.014s -sys 0m21.506s - -CPU UTILIZATION: 25.024 / 28 - ------------------------------------------ - -(60): time { cat f1 | frun -u -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -100000000 -real 0m1.868s -user 0m24.926s -sys 0m21.840s - -CPU UTILIZATION: 25.035 / 28 - ------------------------------------------ - -(61): time { frun -u -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.657s -user 0m1.509s -sys 0m13.777s - -CPU UTILIZATION: 23.266 / 28 - ------------------------------------------ - -(62): time { frun -u -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 392 assigned | 386 processed | 1 I stole | 7 stolen from me -Node 1 (Phys 1): 382 assigned | 385 processed | 5 I stole | 2 stolen from me -Node 2 (Phys 2): 378 assigned | 376 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 375 assigned | 380 processed | 5 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 13 chunks (0.9%) -================================================================= - -real 0m0.704s -user 0m2.396s -sys 0m14.124s - -CPU UTILIZATION: 23.465 / 28 - ------------------------------------------ - -(64): time { cat f1 | frun -u -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 387 processed | 6 I stole | 3 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 5 I stole | 5 stolen from me -Node 2 (Phys 2): 383 assigned | 380 processed | 2 I stole | 5 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 5 I stole | 5 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 18 chunks (1.2%) -================================================================= - -0 -real 0m0.702s -user 0m2.391s -sys 0m14.070s - -CPU UTILIZATION: 23.448 / 28 - ------------------------------------------ - -(65): time { frun -u -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.694s -user 0m2.287s -sys 0m13.985s - -CPU UTILIZATION: 23.446 / 28 - ------------------------------------------ - -(66): time { frun -u -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 387 assigned | 384 processed | 6 I stole | 9 stolen from me -Node 1 (Phys 1): 382 assigned | 380 processed | 9 I stole | 11 stolen from me -Node 2 (Phys 2): 382 assigned | 383 processed | 11 I stole | 10 stolen from me -Node 3 (Phys 3): 376 assigned | 380 processed | 8 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 34 chunks (2.2%) -================================================================= - -real 0m0.740s -user 0m3.140s -sys 0m14.400s - -CPU UTILIZATION: 23.702 / 28 - ------------------------------------------ - -(68): time { cat f1 | frun -u -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 383 assigned | 380 processed | 0 I stole | 3 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 383 processed | 2 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 1 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 4 chunks (0.3%) -================================================================= - -5965 -real 0m0.762s -user 0m3.187s -sys 0m14.209s - -CPU UTILIZATION: 22.829 / 28 - ------------------------------------------ - -(69): time { frun -u -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.402s -user 0m21.278s -sys 0m14.270s - -CPU UTILIZATION: 25.355 / 28 - ------------------------------------------ - -(70): time { frun -u -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -real 0m1.450s -user 0m22.197s -sys 0m14.591s - -CPU UTILIZATION: 25.371 / 28 - ------------------------------------------ - -(72): time { cat f1 | frun -u -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 385 assigned | 384 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 380 assigned | 379 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 378 assigned | 380 processed | 2 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -100000000 -real 0m1.459s -user 0m21.589s -sys 0m14.630s - -CPU UTILIZATION: 24.824 / 28 - ------------------------------------------ - -(73): time { frun -U -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.362s -user 0m34.637s -sys 0m0.722s - -CPU UTILIZATION: 25.961 / 28 - ------------------------------------------ - -(74): time { frun -U -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 386 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 389 assigned | 388 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 376 assigned | 376 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 377 assigned | 377 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -real 0m1.362s -user 0m34.743s -sys 0m0.832s - -CPU UTILIZATION: 26.119 / 28 - ------------------------------------------ - -(76): time { cat f1 | frun -U -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 392 assigned | 392 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 370 assigned | 370 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -0 -real 0m1.370s -user 0m34.954s -sys 0m0.958s - -CPU UTILIZATION: 26.213 / 28 - ------------------------------------------ - -(77): time { frun -U -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.369s -user 0m34.772s -sys 0m0.775s - -CPU UTILIZATION: 25.965 / 28 - ------------------------------------------ - -(78): time { frun -U -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 392 assigned | 392 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 363 assigned | 364 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -real 0m1.368s -user 0m34.963s -sys 0m0.858s - -CPU UTILIZATION: 26.184 / 28 - ------------------------------------------ - -(80): time { cat f1 | frun -U -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 389 assigned | 389 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 371 assigned | 371 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 391 assigned | 391 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 376 assigned | 376 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -25555 -real 0m1.373s -user 0m34.868s -sys 0m1.024s - -CPU UTILIZATION: 26.141 / 28 - ------------------------------------------ - -(81): time { frun -U -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.365s -user 0m34.869s -sys 0m0.775s - -CPU UTILIZATION: 26.112 / 28 - ------------------------------------------ - -(82): time { frun -U -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 387 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 375 assigned | 374 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -real 0m1.373s -user 0m34.984s -sys 0m0.896s - -CPU UTILIZATION: 26.132 / 28 - ------------------------------------------ - -(84): time { cat f1 | frun -U -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 377 assigned | 377 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -25555 -real 0m1.377s -user 0m35.092s -sys 0m0.980s - -CPU UTILIZATION: 26.196 / 28 - ------------------------------------------ - -(85): time { frun -U -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.615s -user 0m41.545s -sys 0m0.557s - -CPU UTILIZATION: 26.069 / 28 - ------------------------------------------ - -(86): time { frun -U -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 390 assigned | 389 processed | 3 I stole | 4 stolen from me -Node 1 (Phys 1): 370 assigned | 369 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 387 assigned | 389 processed | 3 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 8 chunks (0.5%) -================================================================= - -real 0m1.704s -user 0m44.001s -sys 0m0.706s - -CPU UTILIZATION: 26.236 / 28 - ------------------------------------------ - -(88): time { cat f1 | frun -U -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 378 assigned | 378 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 371 assigned | 371 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 392 assigned | 392 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 386 assigned | 386 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -0 -real 0m1.715s -user 0m44.250s -sys 0m0.744s - -CPU UTILIZATION: 26.235 / 28 - ------------------------------------------ - -(89): time { frun -U -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.616s -user 0m41.593s -sys 0m0.540s - -CPU UTILIZATION: 26.072 / 28 - ------------------------------------------ - -(90): time { frun -U -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 379 assigned | 380 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 387 assigned | 386 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 378 assigned | 377 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -real 0m1.707s -user 0m44.058s -sys 0m0.812s - -CPU UTILIZATION: 26.285 / 28 - ------------------------------------------ - -(92): time { cat f1 | frun -U -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 390 assigned | 390 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 374 assigned | 374 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 394 assigned | 395 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 369 assigned | 368 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -5965 -real 0m1.712s -user 0m44.171s -sys 0m0.812s - -CPU UTILIZATION: 26.275 / 28 - ------------------------------------------ - -(93): time { frun -U -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.625s -user 0m41.839s -sys 0m0.505s - -CPU UTILIZATION: 26.057 / 28 - ------------------------------------------ - -(94): time { frun -U -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 367 assigned | 367 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 393 assigned | 393 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.722s -user 0m44.375s -sys 0m0.782s - -CPU UTILIZATION: 26.223 / 28 - ------------------------------------------ - -(96): time { cat f1 | frun -U -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 373 assigned | 375 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 395 assigned | 395 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 391 assigned | 389 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 368 assigned | 368 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.2%) -================================================================= - -5965 -real 0m1.717s -user 0m44.367s -sys 0m0.809s - -CPU UTILIZATION: 26.311 / 28 - ------------------------------------------ - -(97): time { frun -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.167s -user 0m1.744s -sys 0m0.754s - -CPU UTILIZATION: 14.958 / 28 - ------------------------------------------ - -(98): time { frun -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 387 processed | 33 I stole | 30 stolen from me -Node 1 (Phys 1): 370 assigned | 362 processed | 20 I stole | 28 stolen from me -Node 2 (Phys 2): 429 assigned | 444 processed | 38 I stole | 23 stolen from me -Node 3 (Phys 3): 344 assigned | 334 processed | 22 I stole | 32 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 113 chunks (7.4%) -================================================================= - -real 0m0.186s -user 0m1.801s -sys 0m0.948s - -CPU UTILIZATION: 14.779 / 28 - ------------------------------------------ - -(100): time { cat f1 | frun -s : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 367 assigned | 360 processed | 22 I stole | 29 stolen from me -Node 1 (Phys 1): 398 assigned | 406 processed | 25 I stole | 17 stolen from me -Node 2 (Phys 2): 382 assigned | 393 processed | 26 I stole | 15 stolen from me -Node 3 (Phys 3): 380 assigned | 368 processed | 15 I stole | 27 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 88 chunks (5.8%) -================================================================= - -0 -real 0m0.187s -user 0m1.856s -sys 0m0.947s - -CPU UTILIZATION: 14.989 / 28 - ------------------------------------------ - -(101): time { frun -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.746s -user 0m9.124s -sys 0m7.646s - -CPU UTILIZATION: 22.479 / 28 - ------------------------------------------ - -(102): time { frun -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -real 0m0.757s -user 0m9.309s -sys 0m7.683s - -CPU UTILIZATION: 22.446 / 28 - ------------------------------------------ - -(104): time { cat f1 | frun -s cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 379 assigned | 378 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -100000000 -real 0m0.762s -user 0m9.230s -sys 0m7.894s - -CPU UTILIZATION: 22.472 / 28 - ------------------------------------------ - -(105): time { frun -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.739s -user 0m9.091s -sys 0m7.383s - -CPU UTILIZATION: 22.292 / 28 - ------------------------------------------ - -(106): time { frun -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.2%) -================================================================= - -real 0m0.750s -user 0m9.222s -sys 0m7.513s - -CPU UTILIZATION: 22.313 / 28 - ------------------------------------------ - -(108): time { cat f1 | frun -s tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 378 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.1%) -================================================================= - -100000000 -real 0m0.746s -user 0m9.143s -sys 0m7.654s - -CPU UTILIZATION: 22.516 / 28 - ------------------------------------------ - -(109): time { frun -b 524288 : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.112s -user 0m0.052s -sys 0m0.136s - -CPU UTILIZATION: 1.678 / 28 - ------------------------------------------ - -(110): time { frun -b 524288 : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 391 processed | 6 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 378 processed | 0 I stole | 3 stolen from me -Node 3 (Phys 3): 377 assigned | 374 processed | 0 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.4%) -================================================================= - -real 0m0.132s -user 0m0.243s -sys 0m0.258s - -CPU UTILIZATION: 3.795 / 28 - ------------------------------------------ - -(112): time { cat f1 | frun -b 524288 : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 375 processed | 0 I stole | 7 stolen from me -Node 1 (Phys 1): 381 assigned | 378 processed | 3 I stole | 6 stolen from me -Node 2 (Phys 2): 387 assigned | 402 processed | 17 I stole | 2 stolen from me -Node 3 (Phys 3): 377 assigned | 372 processed | 2 I stole | 7 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 22 chunks (1.4%) -================================================================= - -0 -real 0m0.129s -user 0m0.232s -sys 0m0.248s - -CPU UTILIZATION: 3.720 / 28 - ------------------------------------------ - -(113): time { frun -b 524288 cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.114s -user 0m0.098s -sys 0m0.224s - -CPU UTILIZATION: 2.824 / 28 - ------------------------------------------ - -(114): time { frun -b 524288 cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 387 assigned | 385 processed | 1 I stole | 3 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 5 I stole | 4 stolen from me -Node 2 (Phys 2): 383 assigned | 381 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 375 assigned | 378 processed | 5 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 12 chunks (0.8%) -================================================================= - -real 0m0.154s -user 0m0.570s -sys 0m0.584s - -CPU UTILIZATION: 7.493 / 28 - ------------------------------------------ - -(116): time { cat f1 | frun -b 524288 cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 385 assigned | 386 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 376 assigned | 377 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 385 assigned | 384 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 4 chunks (0.3%) -================================================================= - -100000000 -real 0m0.160s -user 0m0.588s -sys 0m0.625s - -CPU UTILIZATION: 7.581 / 28 - ------------------------------------------ - -(117): time { frun -b 524288 tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.114s -user 0m0.092s -sys 0m0.234s - -CPU UTILIZATION: 2.859 / 28 - ------------------------------------------ - -(118): time { frun -b 524288 tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 384 processed | 5 I stole | 3 stolen from me -Node 1 (Phys 1): 382 assigned | 384 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 381 assigned | 378 processed | 1 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 12 chunks (0.8%) -================================================================= - -real 0m0.150s -user 0m0.580s -sys 0m0.563s - -CPU UTILIZATION: 7.620 / 28 - ------------------------------------------ - -(120): time { cat f1 | frun -b 524288 tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 380 assigned | 381 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 2 I stole | 2 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.4%) -================================================================= - -100000000 -real 0m0.148s -user 0m0.582s -sys 0m0.579s - -CPU UTILIZATION: 7.844 / 28 - ------------------------------------------ - -(121): time { frun -b4096 -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.171s -user 0m1.612s -sys 0m0.732s - -CPU UTILIZATION: 13.707 / 28 - ------------------------------------------ - -(122): time { frun -b4096 -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 387 assigned | 398 processed | 19 I stole | 8 stolen from me -Node 1 (Phys 1): 394 assigned | 393 processed | 11 I stole | 12 stolen from me -Node 2 (Phys 2): 380 assigned | 373 processed | 5 I stole | 12 stolen from me -Node 3 (Phys 3): 366 assigned | 363 processed | 6 I stole | 9 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 41 chunks (2.7%) -================================================================= - -real 0m0.176s -user 0m1.712s -sys 0m0.770s - -CPU UTILIZATION: 14.102 / 28 - ------------------------------------------ - -(124): time { cat f1 | frun -b4096 -s : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 412 assigned | 412 processed | 25 I stole | 25 stolen from me -Node 1 (Phys 1): 399 assigned | 383 processed | 16 I stole | 32 stolen from me -Node 2 (Phys 2): 362 assigned | 370 processed | 21 I stole | 13 stolen from me -Node 3 (Phys 3): 354 assigned | 362 processed | 23 I stole | 15 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 85 chunks (5.6%) -================================================================= - -0 -real 0m0.181s -user 0m1.686s -sys 0m0.811s - -CPU UTILIZATION: 13.795 / 28 - ------------------------------------------ - -(125): time { frun -b4096 -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.724s -user 0m8.780s -sys 0m7.117s - -CPU UTILIZATION: 21.957 / 28 - ------------------------------------------ - -(126): time { frun -b4096 -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 381 assigned | 383 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.2%) -================================================================= - -real 0m0.726s -user 0m8.695s -sys 0m7.454s - -CPU UTILIZATION: 22.243 / 28 - ------------------------------------------ - -(128): time { cat f1 | frun -b4096 -s cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 382 assigned | 380 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 380 assigned | 382 processed | 2 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 4 chunks (0.3%) -================================================================= - -100000000 -real 0m0.728s -user 0m8.798s -sys 0m7.454s - -CPU UTILIZATION: 22.324 / 28 - ------------------------------------------ - -(129): time { frun -b4096 -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.715s -user 0m8.725s -sys 0m6.:00s - -CPU UTILIZATION: 13.041 / 28 - ------------------------------------------ - -(130): time { frun -b4096 -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 384 processed | 2 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.2%) -================================================================= - -real 0m0.713s -user 0m8.705s -sys 0m7.151s - -CPU UTILIZATION: 22.238 / 28 - ------------------------------------------ - -(132): time { cat f1 | frun -b4096 -s tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -100000000 -real 0m0.717s -user 0m8.741s -sys 0m7.275s - -CPU UTILIZATION: 22.337 / 28 - ------------------------------------------ - -(133): time { frun -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.204s -user 0m6.041s -sys 0m23.034s - -CPU UTILIZATION: 24.148 / 28 - ------------------------------------------ - -(134): time { frun -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3420 assigned | 3451 processed | 173 I stole | 142 stolen from me -Node 1 (Phys 1): 3325 assigned | 3284 processed | 128 I stole | 169 stolen from me -Node 2 (Phys 2): 3388 assigned | 3392 processed | 161 I stole | 157 stolen from me -Node 3 (Phys 3): 3432 assigned | 3438 processed | 150 I stole | 144 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 612 chunks (4.5%) -================================================================= - -real 0m1.355s -user 0m9.210s -sys 0m23.677s - -CPU UTILIZATION: 24.270 / 28 - ------------------------------------------ - -(136): time { cat f2 | frun -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3385 assigned | 3381 processed | 157 I stole | 161 stolen from me -Node 1 (Phys 1): 3382 assigned | 3374 processed | 158 I stole | 166 stolen from me -Node 2 (Phys 2): 3397 assigned | 3400 processed | 150 I stole | 147 stolen from me -Node 3 (Phys 3): 3401 assigned | 3410 processed | 141 I stole | 132 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 606 chunks (4.5%) -================================================================= - -0 -real 0m1.353s -user 0m9.157s -sys 0m23.733s - -CPU UTILIZATION: 24.308 / 28 - ------------------------------------------ - -(137): time { frun -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.328s -user 0m7.465s -sys 0m24.798s - -CPU UTILIZATION: 24.294 / 28 - ------------------------------------------ - -(138): time { frun -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3353 assigned | 3314 processed | 196 I stole | 235 stolen from me -Node 1 (Phys 1): 3352 assigned | 3365 processed | 208 I stole | 195 stolen from me -Node 2 (Phys 2): 3431 assigned | 3418 processed | 181 I stole | 194 stolen from me -Node 3 (Phys 3): 3429 assigned | 3468 processed | 215 I stole | 176 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 800 chunks (5.9%) -================================================================= - -real 0m1.473s -user 0m10.111s -sys 0m26.130s - -CPU UTILIZATION: 24.603 / 28 - ------------------------------------------ - -(140): time { cat f2 | frun -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3247 assigned | 3229 processed | 196 I stole | 214 stolen from me -Node 1 (Phys 1): 3378 assigned | 3405 processed | 212 I stole | 185 stolen from me -Node 2 (Phys 2): 3478 assigned | 3449 processed | 164 I stole | 193 stolen from me -Node 3 (Phys 3): 3462 assigned | 3482 processed | 190 I stole | 170 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 762 chunks (5.6%) -================================================================= - -28350 -real 0m1.537s -user 0m10.111s -sys 0m26.881s - -CPU UTILIZATION: 24.067 / 28 - ------------------------------------------ - -(141): time { frun -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m2.083s -user 0m27.585s -sys 0m24.954s - -CPU UTILIZATION: 25.222 / 28 - ------------------------------------------ - -(142): time { frun -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3414 assigned | 3395 processed | 188 I stole | 207 stolen from me -Node 1 (Phys 1): 3419 assigned | 3406 processed | 190 I stole | 203 stolen from me -Node 2 (Phys 2): 3396 assigned | 3399 processed | 211 I stole | 208 stolen from me -Node 3 (Phys 3): 3336 assigned | 3365 processed | 189 I stole | 160 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 778 chunks (5.7%) -================================================================= - -real 0m2.201s -user 0m29.862s -sys 0m26.211s - -CPU UTILIZATION: 25.476 / 28 - ------------------------------------------ - -(144): time { cat f2 | frun -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3390 assigned | 3400 processed | 200 I stole | 190 stolen from me -Node 1 (Phys 1): 3418 assigned | 3401 processed | 192 I stole | 209 stolen from me -Node 2 (Phys 2): 3386 assigned | 3373 processed | 181 I stole | 194 stolen from me -Node 3 (Phys 3): 3371 assigned | 3391 processed | 196 I stole | 176 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 769 chunks (5.7%) -================================================================= - -100000000 -real 0m2.214s -user 0m29.844s -sys 0m26.741s - -CPU UTILIZATION: 25.557 / 28 - ------------------------------------------ - -(145): time { frun -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 104 assigned | 104 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.741s -user 0m1.948s -sys 0m15.674s - -CPU UTILIZATION: 23.781 / 28 - ------------------------------------------ - -(146): time { frun -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3482 assigned | 3447 processed | 222 I stole | 257 stolen from me -Node 1 (Phys 1): 3338 assigned | 3327 processed | 234 I stole | 245 stolen from me -Node 2 (Phys 2): 3324 assigned | 3307 processed | 240 I stole | 257 stolen from me -Node 3 (Phys 3): 3421 assigned | 3484 processed | 274 I stole | 211 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 970 chunks (7.2%) -================================================================= - -real 0m1.088s -user 0m4.836s -sys 0m20.383s - -CPU UTILIZATION: 23.179 / 28 - ------------------------------------------ - -(148): time { cat f2 | frun -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3391 assigned | 3381 processed | 257 I stole | 267 stolen from me -Node 1 (Phys 1): 3381 assigned | 3414 processed | 250 I stole | 217 stolen from me -Node 2 (Phys 2): 3404 assigned | 3377 processed | 192 I stole | 219 stolen from me -Node 3 (Phys 3): 3389 assigned | 3393 processed | 206 I stole | 202 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 905 chunks (6.7%) -================================================================= - -0 -real 0m1.080s -user 0m4.764s -sys 0m20.402s - -CPU UTILIZATION: 23.301 / 28 - ------------------------------------------ - -(149): time { frun -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.828s -user 0m3.531s -sys 0m16.539s - -CPU UTILIZATION: 24.239 / 28 - ------------------------------------------ - -(150): time { frun -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3362 assigned | 3363 processed | 222 I stole | 221 stolen from me -Node 1 (Phys 1): 3402 assigned | 3432 processed | 235 I stole | 205 stolen from me -Node 2 (Phys 2): 3416 assigned | 3372 processed | 178 I stole | 222 stolen from me -Node 3 (Phys 3): 3385 assigned | 3398 processed | 220 I stole | 207 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 855 chunks (6.3%) -================================================================= - -real 0m1.190s -user 0m6.196s -sys 0m21.820s - -CPU UTILIZATION: 23.542 / 28 - ------------------------------------------ - -(152): time { cat f2 | frun -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3422 assigned | 3432 processed | 248 I stole | 238 stolen from me -Node 1 (Phys 1): 3404 assigned | 3385 processed | 217 I stole | 236 stolen from me -Node 2 (Phys 2): 3308 assigned | 3318 processed | 236 I stole | 226 stolen from me -Node 3 (Phys 3): 3431 assigned | 3430 processed | 195 I stole | 196 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 896 chunks (6.6%) -================================================================= - -14837 -real 0m1.223s -user 0m6.308s -sys 0m22.387s - -CPU UTILIZATION: 23.462 / 28 - ------------------------------------------ - -(153): time { frun -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.606s -user 0m24.114s -sys 0m16.960s - -CPU UTILIZATION: 25.575 / 28 - ------------------------------------------ - -(154): time { frun -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3396 assigned | 3369 processed | 277 I stole | 304 stolen from me -Node 1 (Phys 1): 3360 assigned | 3366 processed | 299 I stole | 293 stolen from me -Node 2 (Phys 2): 3418 assigned | 3410 processed | 282 I stole | 290 stolen from me -Node 3 (Phys 3): 3391 assigned | 3420 processed | 276 I stole | 247 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1134 chunks (8.4%) -================================================================= - -real 0m1.899s -user 0m27.216s -sys 0m21.161s - -CPU UTILIZATION: 25.474 / 28 - ------------------------------------------ - -(156): time { cat f2 | frun -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3422 assigned | 3405 processed | 354 I stole | 371 stolen from me -Node 1 (Phys 1): 3395 assigned | 3388 processed | 350 I stole | 357 stolen from me -Node 2 (Phys 2): 3393 assigned | 3393 processed | 339 I stole | 339 stolen from me -Node 3 (Phys 3): 3355 assigned | 3379 processed | 331 I stole | 307 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1374 chunks (10.1%) -================================================================= - -100000000 -real 0m1.947s -user 0m27.369s -sys 0m21.511s - -CPU UTILIZATION: 25.105 / 28 - ------------------------------------------ - -(157): time { frun -k -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.221s -user 0m5.989s -sys 0m23.087s - -CPU UTILIZATION: 23.813 / 28 - ------------------------------------------ - -(158): time { frun -k -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3375 assigned | 3326 processed | 163 I stole | 212 stolen from me -Node 1 (Phys 1): 3438 assigned | 3446 processed | 182 I stole | 174 stolen from me -Node 2 (Phys 2): 3411 assigned | 3437 processed | 191 I stole | 165 stolen from me -Node 3 (Phys 3): 3341 assigned | 3356 processed | 168 I stole | 153 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 704 chunks (5.2%) -================================================================= - -real 0m1.352s -user 0m9.282s -sys 0m23.526s - -CPU UTILIZATION: 24.266 / 28 - ------------------------------------------ - -(160): time { cat f2 | frun -k -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3409 assigned | 3421 processed | 162 I stole | 150 stolen from me -Node 1 (Phys 1): 3405 assigned | 3399 processed | 156 I stole | 162 stolen from me -Node 2 (Phys 2): 3403 assigned | 3401 processed | 155 I stole | 157 stolen from me -Node 3 (Phys 3): 3348 assigned | 3344 processed | 130 I stole | 134 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 603 chunks (4.4%) -================================================================= - -0 -real 0m1.354s -user 0m9.253s -sys 0m23.648s - -CPU UTILIZATION: 24.299 / 28 - ------------------------------------------ - -(161): time { frun -k -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.335s -user 0m7.432s -sys 0m24.908s - -CPU UTILIZATION: 24.224 / 28 - ------------------------------------------ - -(162): time { frun -k -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3409 assigned | 3381 processed | 182 I stole | 210 stolen from me -Node 1 (Phys 1): 3392 assigned | 3383 processed | 188 I stole | 197 stolen from me -Node 2 (Phys 2): 3365 assigned | 3381 processed | 200 I stole | 184 stolen from me -Node 3 (Phys 3): 3399 assigned | 3420 processed | 199 I stole | 178 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 769 chunks (5.7%) -================================================================= - -real 0m1.478s -user 0m9.994s -sys 0m26.197s - -CPU UTILIZATION: 24.486 / 28 - ------------------------------------------ - -(164): time { cat f2 | frun -k -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3426 assigned | 3392 processed | 189 I stole | 223 stolen from me -Node 1 (Phys 1): 3412 assigned | 3399 processed | 192 I stole | 205 stolen from me -Node 2 (Phys 2): 3398 assigned | 3372 processed | 172 I stole | 198 stolen from me -Node 3 (Phys 3): 3329 assigned | 3402 processed | 238 I stole | 165 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 791 chunks (5.8%) -================================================================= - -28349 -real 0m1.483s -user 0m9.981s -sys 0m26.630s - -CPU UTILIZATION: 24.687 / 28 - ------------------------------------------ - -(165): time { frun -k -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m2.080s -user 0m27.580s -sys 0m24.995s - -CPU UTILIZATION: 25.276 / 28 - ------------------------------------------ - -(166): time { frun -k -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3431 assigned | 3406 processed | 209 I stole | 234 stolen from me -Node 1 (Phys 1): 3370 assigned | 3390 processed | 222 I stole | 202 stolen from me -Node 2 (Phys 2): 3389 assigned | 3373 processed | 201 I stole | 217 stolen from me -Node 3 (Phys 3): 3375 assigned | 3396 processed | 188 I stole | 167 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 820 chunks (6.0%) -================================================================= - -real 0m2.204s -user 0m29.851s -sys 0m26.179s - -CPU UTILIZATION: 25.421 / 28 - ------------------------------------------ - -(168): time { cat f2 | frun -k -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3399 assigned | 3410 processed | 200 I stole | 189 stolen from me -Node 1 (Phys 1): 3432 assigned | 3406 processed | 164 I stole | 190 stolen from me -Node 2 (Phys 2): 3388 assigned | 3383 processed | 154 I stole | 159 stolen from me -Node 3 (Phys 3): 3346 assigned | 3366 processed | 178 I stole | 158 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 696 chunks (5.1%) -================================================================= - -100000000 -real 0m2.210s -user 0m29.683s -sys 0m26.780s - -CPU UTILIZATION: 25.548 / 28 - ------------------------------------------ - -(169): time { frun -k -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.737s -user 0m1.945s -sys 0m15.645s - -CPU UTILIZATION: 23.867 / 28 - ------------------------------------------ - -(170): time { frun -k -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3423 assigned | 3448 processed | 285 I stole | 260 stolen from me -Node 1 (Phys 1): 3397 assigned | 3376 processed | 242 I stole | 263 stolen from me -Node 2 (Phys 2): 3404 assigned | 3395 processed | 216 I stole | 225 stolen from me -Node 3 (Phys 3): 3341 assigned | 3346 processed | 244 I stole | 239 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 987 chunks (7.3%) -================================================================= - -real 0m1.074s -user 0m4.793s -sys 0m20.409s - -CPU UTILIZATION: 23.465 / 28 - ------------------------------------------ - -(172): time { cat f2 | frun -k -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3426 assigned | 3425 processed | 184 I stole | 185 stolen from me -Node 1 (Phys 1): 3524 assigned | 3521 processed | 191 I stole | 194 stolen from me -Node 2 (Phys 2): 3412 assigned | 3453 processed | 217 I stole | 176 stolen from me -Node 3 (Phys 3): 3203 assigned | 3166 processed | 176 I stole | 213 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 768 chunks (5.7%) -================================================================= - -0 -real 0m1.381s -user 0m4.867s -sys 0m20.686s - -CPU UTILIZATION: 18.503 / 28 - ------------------------------------------ - -(173): time { frun -k -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.837s -user 0m3.429s -sys 0m16.627s - -CPU UTILIZATION: 23.961 / 28 - ------------------------------------------ - -(174): time { frun -k -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3455 assigned | 3453 processed | 257 I stole | 259 stolen from me -Node 1 (Phys 1): 3360 assigned | 3345 processed | 248 I stole | 263 stolen from me -Node 2 (Phys 2): 3343 assigned | 3346 processed | 248 I stole | 245 stolen from me -Node 3 (Phys 3): 3407 assigned | 3421 processed | 227 I stole | 213 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 980 chunks (7.2%) -================================================================= - -real 0m1.179s -user 0m6.184s -sys 0m21.864s - -CPU UTILIZATION: 23.789 / 28 - ------------------------------------------ - -(176): time { cat f2 | frun -k -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3432 assigned | 3385 processed | 262 I stole | 309 stolen from me -Node 1 (Phys 1): 3400 assigned | 3385 processed | 277 I stole | 292 stolen from me -Node 2 (Phys 2): 3351 assigned | 3357 processed | 250 I stole | 244 stolen from me -Node 3 (Phys 3): 3382 assigned | 3438 processed | 261 I stole | 205 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1050 chunks (7.7%) -================================================================= - -14836 -real 0m1.195s -user 0m6.293s -sys 0m22.242s - -CPU UTILIZATION: 23.878 / 28 - ------------------------------------------ - -(177): time { frun -k -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.599s -user 0m24.071s -sys 0m16.968s - -CPU UTILIZATION: 25.665 / 28 - ------------------------------------------ - -(178): time { frun -k -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3411 assigned | 3393 processed | 353 I stole | 371 stolen from me -Node 1 (Phys 1): 3426 assigned | 3402 processed | 329 I stole | 353 stolen from me -Node 2 (Phys 2): 3409 assigned | 3365 processed | 323 I stole | 367 stolen from me -Node 3 (Phys 3): 3319 assigned | 3405 processed | 365 I stole | 279 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1370 chunks (10.1%) -================================================================= - -real 0m1.902s -user 0m27.209s -sys 0m21.178s - -CPU UTILIZATION: 25.440 / 28 - ------------------------------------------ - -(180): time { cat f2 | frun -k -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3372 assigned | 3358 processed | 380 I stole | 394 stolen from me -Node 1 (Phys 1): 3393 assigned | 3411 processed | 405 I stole | 387 stolen from me -Node 2 (Phys 2): 3401 assigned | 3364 processed | 350 I stole | 387 stolen from me -Node 3 (Phys 3): 3399 assigned | 3432 processed | 346 I stole | 313 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1481 chunks (10.9%) -================================================================= - -100000000 -real 0m1.907s -user 0m27.312s -sys 0m21.565s - -CPU UTILIZATION: 25.630 / 28 - ------------------------------------------ - -(181): time { frun -u -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.179s -user 0m5.690s -sys 0m22.638s - -CPU UTILIZATION: 24.027 / 28 - ------------------------------------------ - -(182): time { frun -u -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3410 assigned | 3405 processed | 173 I stole | 178 stolen from me -Node 1 (Phys 1): 3314 assigned | 3292 processed | 153 I stole | 175 stolen from me -Node 2 (Phys 2): 3435 assigned | 3418 processed | 156 I stole | 173 stolen from me -Node 3 (Phys 3): 3406 assigned | 3450 processed | 178 I stole | 134 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 660 chunks (4.9%) -================================================================= - -real 0m1.323s -user 0m8.810s -sys 0m23.223s - -CPU UTILIZATION: 24.212 / 28 - ------------------------------------------ - -(184): time { cat f2 | frun -u -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3410 assigned | 3408 processed | 185 I stole | 187 stolen from me -Node 1 (Phys 1): 3328 assigned | 3282 processed | 167 I stole | 213 stolen from me -Node 2 (Phys 2): 3378 assigned | 3410 processed | 190 I stole | 158 stolen from me -Node 3 (Phys 3): 3449 assigned | 3465 processed | 183 I stole | 167 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 725 chunks (5.3%) -================================================================= - -0 -real 0m1.326s -user 0m8.747s -sys 0m23.365s - -CPU UTILIZATION: 24.217 / 28 - ------------------------------------------ - -(185): time { frun -u -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.266s -user 0m6.914s -sys 0m23.887s - -CPU UTILIZATION: 24.329 / 28 - ------------------------------------------ - -(186): time { frun -u -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3416 assigned | 3390 processed | 172 I stole | 198 stolen from me -Node 1 (Phys 1): 3462 assigned | 3417 processed | 149 I stole | 194 stolen from me -Node 2 (Phys 2): 3363 assigned | 3371 processed | 164 I stole | 156 stolen from me -Node 3 (Phys 3): 3324 assigned | 3387 processed | 200 I stole | 137 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 685 chunks (5.0%) -================================================================= - -real 0m1.414s -user 0m9.579s -sys 0m24.945s - -CPU UTILIZATION: 24.415 / 28 - ------------------------------------------ - -(188): time { cat f2 | frun -u -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3375 assigned | 3386 processed | 95 I stole | 84 stolen from me -Node 1 (Phys 1): 3390 assigned | 3393 processed | 91 I stole | 88 stolen from me -Node 2 (Phys 2): 3416 assigned | 3389 processed | 66 I stole | 93 stolen from me -Node 3 (Phys 3): 3384 assigned | 3397 processed | 78 I stole | 65 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 330 chunks (2.4%) -================================================================= - -28350 -real 0m1.483s -user 0m9.546s -sys 0m25.123s - -CPU UTILIZATION: 23.377 / 28 - ------------------------------------------ - -(189): time { frun -u -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m2.015s -user 0m27.280s -sys 0m23.589s - -CPU UTILIZATION: 25.245 / 28 - ------------------------------------------ - -(190): time { frun -u -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3413 assigned | 3393 processed | 213 I stole | 233 stolen from me -Node 1 (Phys 1): 3407 assigned | 3399 processed | 174 I stole | 182 stolen from me -Node 2 (Phys 2): 3372 assigned | 3385 processed | 191 I stole | 178 stolen from me -Node 3 (Phys 3): 3373 assigned | 3388 processed | 191 I stole | 176 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 769 chunks (5.7%) -================================================================= - -real 0m2.140s -user 0m29.077s -sys 0m25.250s - -CPU UTILIZATION: 25.386 / 28 - ------------------------------------------ - -(192): time { cat f2 | frun -u -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3405 assigned | 3405 processed | 19 I stole | 19 stolen from me -Node 1 (Phys 1): 3408 assigned | 3398 processed | 16 I stole | 26 stolen from me -Node 2 (Phys 2): 3363 assigned | 3370 processed | 18 I stole | 11 stolen from me -Node 3 (Phys 3): 3389 assigned | 3392 processed | 21 I stole | 18 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 74 chunks (0.5%) -================================================================= - -100000000 -real 0m2.344s -user 0m26.830s -sys 0m26.918s - -CPU UTILIZATION: 22.930 / 28 - ------------------------------------------ - -(193): time { frun -u -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.732s -user 0m1.825s -sys 0m15.584s - -CPU UTILIZATION: 23.782 / 28 - ------------------------------------------ - -(194): time { frun -u -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3378 assigned | 3386 processed | 287 I stole | 279 stolen from me -Node 1 (Phys 1): 3453 assigned | 3360 processed | 239 I stole | 332 stolen from me -Node 2 (Phys 2): 3411 assigned | 3468 processed | 309 I stole | 252 stolen from me -Node 3 (Phys 3): 3323 assigned | 3351 processed | 293 I stole | 265 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1128 chunks (8.3%) -================================================================= - -real 0m1.047s -user 0m4.571s -sys 0m20.148s - -CPU UTILIZATION: 23.609 / 28 - ------------------------------------------ - -(196): time { cat f2 | frun -u -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3408 assigned | 3404 processed | 288 I stole | 292 stolen from me -Node 1 (Phys 1): 3417 assigned | 3444 processed | 278 I stole | 251 stolen from me -Node 2 (Phys 2): 3389 assigned | 3355 processed | 243 I stole | 277 stolen from me -Node 3 (Phys 3): 3351 assigned | 3362 processed | 244 I stole | 233 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1053 chunks (7.8%) -================================================================= - -0 -real 0m1.049s -user 0m4.544s -sys 0m20.218s - -CPU UTILIZATION: 23.605 / 28 - ------------------------------------------ - -(197): time { frun -u -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.799s -user 0m3.354s -sys 0m15.929s - -CPU UTILIZATION: 24.133 / 28 - ------------------------------------------ - -(198): time { frun -u -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3446 assigned | 3445 processed | 289 I stole | 290 stolen from me -Node 1 (Phys 1): 3349 assigned | 3332 processed | 272 I stole | 289 stolen from me -Node 2 (Phys 2): 3429 assigned | 3398 processed | 246 I stole | 277 stolen from me -Node 3 (Phys 3): 3341 assigned | 3390 processed | 271 I stole | 222 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1078 chunks (7.9%) -================================================================= - -real 0m1.136s -user 0m5.842s -sys 0m20.940s - -CPU UTILIZATION: 23.575 / 28 - ------------------------------------------ - -(200): time { cat f2 | frun -u -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3450 assigned | 3456 processed | 190 I stole | 184 stolen from me -Node 1 (Phys 1): 3399 assigned | 3386 processed | 168 I stole | 181 stolen from me -Node 2 (Phys 2): 3326 assigned | 3336 processed | 167 I stole | 157 stolen from me -Node 3 (Phys 3): 3390 assigned | 3387 processed | 145 I stole | 148 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 670 chunks (4.9%) -================================================================= - -14835 -real 0m1.194s -user 0m5.780s -sys 0m21.798s - -CPU UTILIZATION: 23.097 / 28 - ------------------------------------------ - -(201): time { frun -u -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.568s -user 0m24.162s -sys 0m16.128s - -CPU UTILIZATION: 25.695 / 28 - ------------------------------------------ - -(202): time { frun -u -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3372 assigned | 3378 processed | 361 I stole | 355 stolen from me -Node 1 (Phys 1): 3454 assigned | 3424 processed | 341 I stole | 371 stolen from me -Node 2 (Phys 2): 3382 assigned | 3396 processed | 345 I stole | 331 stolen from me -Node 3 (Phys 3): 3357 assigned | 3367 processed | 334 I stole | 324 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1381 chunks (10.2%) -================================================================= - -real 0m1.855s -user 0m26.843s -sys 0m20.289s - -CPU UTILIZATION: 25.408 / 28 - ------------------------------------------ - -(204): time { cat f2 | frun -u -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3406 assigned | 3412 processed | 132 I stole | 126 stolen from me -Node 1 (Phys 1): 3366 assigned | 3374 processed | 99 I stole | 91 stolen from me -Node 2 (Phys 2): 3406 assigned | 3385 processed | 79 I stole | 100 stolen from me -Node 3 (Phys 3): 3387 assigned | 3394 processed | 84 I stole | 77 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 394 chunks (2.9%) -================================================================= - -100000000 -real 0m2.063s -user 0m24.849s -sys 0m21.479s - -CPU UTILIZATION: 22.456 / 28 - ------------------------------------------ - -(205): time { frun -U -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 103 assigned | 103 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m4.307s -user 1m55.423s -sys 0m1.773s - -CPU UTILIZATION: 27.210 / 28 - ------------------------------------------ - -(206): time { frun -U -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3239 assigned | 3244 processed | 9 I stole | 4 stolen from me -Node 1 (Phys 1): 3456 assigned | 3458 processed | 6 I stole | 4 stolen from me -Node 2 (Phys 2): 3462 assigned | 3460 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 3408 assigned | 3403 processed | 1 I stole | 6 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 17 chunks (0.1%) -================================================================= - -real 0m4.397s -user 1m57.349s -sys 0m2.445s - -CPU UTILIZATION: 27.244 / 28 - ------------------------------------------ - -(208): time { cat f2 | frun -U -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3432 assigned | 3434 processed | 3 I stole | 1 stolen from me -Node 1 (Phys 1): 3351 assigned | 3350 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 3506 assigned | 3506 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 3276 assigned | 3275 processed | 1 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.0%) -================================================================= - -0 -real 0m4.414s -user 1m58.044s -sys 0m2.375s - -CPU UTILIZATION: 27.281 / 28 - ------------------------------------------ - -(209): time { frun -U -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m4.737s -user 2m6.393s -sys 0m2.662s - -CPU UTILIZATION: 27.244 / 28 - ------------------------------------------ - -(210): time { frun -U -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3343 assigned | 3352 processed | 34 I stole | 25 stolen from me -Node 1 (Phys 1): 3410 assigned | 3404 processed | 18 I stole | 24 stolen from me -Node 2 (Phys 2): 3462 assigned | 3461 processed | 17 I stole | 18 stolen from me -Node 3 (Phys 3): 3350 assigned | 3348 processed | 18 I stole | 20 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 87 chunks (0.6%) -================================================================= - -real 0m4.843s -user 2m8.738s -sys 0m3.372s - -CPU UTILIZATION: 27.278 / 28 - ------------------------------------------ - -(212): time { cat f2 | frun -U -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3380 assigned | 3380 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 3509 assigned | 3509 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 3506 assigned | 3506 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3170 assigned | 3170 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -28350 -real 0m4.863s -user 2m9.372s -sys 0m3.501s - -CPU UTILIZATION: 27.323 / 28 - ------------------------------------------ - -(213): time { frun -U -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m8.251s -user 2m53.146s -sys 0m52.966s - -CPU UTILIZATION: 27.404 / 28 - ------------------------------------------ - -(214): time { frun -U -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3451 assigned | 3454 processed | 3 I stole | 0 stolen from me -Node 1 (Phys 1): 3385 assigned | 3383 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 3438 assigned | 3437 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 3291 assigned | 3291 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.0%) -================================================================= - -real 0m8.263s -user 2m53.561s -sys 0m53.514s - -CPU UTILIZATION: 27.480 / 28 - ------------------------------------------ - -(216): time { cat f2 | frun -U -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3482 assigned | 3483 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 3323 assigned | 3323 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 3306 assigned | 3305 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 3454 assigned | 3454 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.0%) -================================================================= - -100000000 -real 0m8.252s -user 2m52.989s -sys 0m54.012s - -CPU UTILIZATION: 27.508 / 28 - ------------------------------------------ - -(217): time { frun -U -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m4.653s -user 2m4.330s -sys 0m1.668s - -CPU UTILIZATION: 27.078 / 28 - ------------------------------------------ - -(218): time { frun -U -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3401 assigned | 3399 processed | 61 I stole | 63 stolen from me -Node 1 (Phys 1): 3420 assigned | 3401 processed | 47 I stole | 66 stolen from me -Node 2 (Phys 2): 3364 assigned | 3381 processed | 56 I stole | 39 stolen from me -Node 3 (Phys 3): 3380 assigned | 3384 processed | 43 I stole | 39 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 207 chunks (1.5%) -================================================================= - -real 0m4.397s -user 1m57.185s -sys 0m2.236s - -CPU UTILIZATION: 27.159 / 28 - ------------------------------------------ - -(220): time { cat f2 | frun -U -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3405 assigned | 3378 processed | 57 I stole | 84 stolen from me -Node 1 (Phys 1): 3374 assigned | 3370 processed | 73 I stole | 77 stolen from me -Node 2 (Phys 2): 3436 assigned | 3455 processed | 59 I stole | 40 stolen from me -Node 3 (Phys 3): 3350 assigned | 3362 processed | 79 I stole | 67 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 268 chunks (2.0%) -================================================================= - -0 -real 0m4.392s -user 1m56.734s -sys 0m2.241s - -CPU UTILIZATION: 27.089 / 28 - ------------------------------------------ - -(221): time { frun -U -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m5.038s -user 2m14.129s -sys 0m2.400s - -CPU UTILIZATION: 27.099 / 28 - ------------------------------------------ - -(222): time { frun -U -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3403 assigned | 3391 processed | 78 I stole | 90 stolen from me -Node 1 (Phys 1): 3435 assigned | 3422 processed | 75 I stole | 88 stolen from me -Node 2 (Phys 2): 3458 assigned | 3473 processed | 104 I stole | 89 stolen from me -Node 3 (Phys 3): 3269 assigned | 3279 processed | 82 I stole | 72 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 339 chunks (2.5%) -================================================================= - -real 0m4.836s -user 2m7.843s -sys 0m3.057s - -CPU UTILIZATION: 27.067 / 28 - ------------------------------------------ - -(224): time { cat f2 | frun -U -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3448 assigned | 3446 processed | 38 I stole | 40 stolen from me -Node 1 (Phys 1): 3418 assigned | 3415 processed | 46 I stole | 49 stolen from me -Node 2 (Phys 2): 3295 assigned | 3307 processed | 46 I stole | 34 stolen from me -Node 3 (Phys 3): 3404 assigned | 3397 processed | 40 I stole | 47 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 170 chunks (1.3%) -================================================================= - -14835 -real 0m4.844s -user 2m8.286s -sys 0m3.300s - -CPU UTILIZATION: 27.164 / 28 - ------------------------------------------ - -(225): time { frun -U -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m8.289s -user 2m55.714s -sys 0m50.142s - -CPU UTILIZATION: 27.247 / 28 - ------------------------------------------ - -(226): time { frun -U -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3465 assigned | 3447 processed | 25 I stole | 43 stolen from me -Node 1 (Phys 1): 3392 assigned | 3394 processed | 41 I stole | 39 stolen from me -Node 2 (Phys 2): 3362 assigned | 3376 processed | 38 I stole | 24 stolen from me -Node 3 (Phys 3): 3346 assigned | 3348 processed | 37 I stole | 35 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 141 chunks (1.0%) -================================================================= - -real 0m8.206s -user 2m53.318s -sys 0m51.899s - -CPU UTILIZATION: 27.445 / 28 - ------------------------------------------ - -(228): time { cat f2 | frun -U -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3419 assigned | 3418 processed | 25 I stole | 26 stolen from me -Node 1 (Phys 1): 3314 assigned | 3321 processed | 27 I stole | 20 stolen from me -Node 2 (Phys 2): 3465 assigned | 3465 processed | 24 I stole | 24 stolen from me -Node 3 (Phys 3): 3367 assigned | 3361 processed | 17 I stole | 23 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 93 chunks (0.7%) -================================================================= - -100000000 -real 0m8.212s -user 2m52.964s -sys 0m52.710s - -CPU UTILIZATION: 27.481 / 28 - ------------------------------------------ - -(229): time { frun -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.2%) -================================================================= - -real 0m0.414s -user 0m1.336s -sys 0m1.421s - -CPU UTILIZATION: 6.659 / 28 - ------------------------------------------ - -(230): time { frun -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3385 assigned | 3391 processed | 6 I stole | 0 stolen from me -Node 1 (Phys 1): 3398 assigned | 3405 processed | 8 I stole | 1 stolen from me -Node 2 (Phys 2): 3397 assigned | 3390 processed | 1 I stole | 8 stolen from me -Node 3 (Phys 3): 3385 assigned | 3379 processed | 0 I stole | 6 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 15 chunks (0.1%) -================================================================= - -real 0m0.564s -user 0m4.027s -sys 0m3.663s - -CPU UTILIZATION: 13.634 / 28 - ------------------------------------------ - -(232): time { cat f2 | frun -s : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3397 assigned | 3397 processed | 4 I stole | 4 stolen from me -Node 1 (Phys 1): 3393 assigned | 3405 processed | 15 I stole | 3 stolen from me -Node 2 (Phys 2): 3382 assigned | 3376 processed | 0 I stole | 6 stolen from me -Node 3 (Phys 3): 3393 assigned | 3387 processed | 1 I stole | 7 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 20 chunks (0.1%) -================================================================= - -0 -real 0m0.548s -user 0m4.042s -sys 0m3.554s - -CPU UTILIZATION: 13.861 / 28 - ------------------------------------------ - -(233): time { frun -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.826s -user 0m9.417s -sys 0m9.454s - -CPU UTILIZATION: 22.846 / 28 - ------------------------------------------ - -(234): time { frun -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3409 assigned | 3394 processed | 101 I stole | 116 stolen from me -Node 1 (Phys 1): 3423 assigned | 3463 processed | 125 I stole | 85 stolen from me -Node 2 (Phys 2): 3319 assigned | 3298 processed | 99 I stole | 120 stolen from me -Node 3 (Phys 3): 3414 assigned | 3410 processed | 85 I stole | 89 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 410 chunks (3.0%) -================================================================= - -real 0m1.005s -user 0m12.093s -sys 0m11.032s - -CPU UTILIZATION: 23.009 / 28 - ------------------------------------------ - -(236): time { cat f2 | frun -s cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3394 assigned | 3381 processed | 114 I stole | 127 stolen from me -Node 1 (Phys 1): 3409 assigned | 3411 processed | 121 I stole | 119 stolen from me -Node 2 (Phys 2): 3403 assigned | 3435 processed | 126 I stole | 94 stolen from me -Node 3 (Phys 3): 3359 assigned | 3338 processed | 93 I stole | 114 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 454 chunks (3.3%) -================================================================= - -100000000 -real 0m1.018s -user 0m12.203s -sys 0m11.424s - -CPU UTILIZATION: 23.209 / 28 - ------------------------------------------ - -(237): time { frun -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.812s -user 0m9.489s -sys 0m8.993s - -CPU UTILIZATION: 22.761 / 28 - ------------------------------------------ - -(238): time { frun -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3425 assigned | 3422 processed | 84 I stole | 87 stolen from me -Node 1 (Phys 1): 3426 assigned | 3414 processed | 79 I stole | 91 stolen from me -Node 2 (Phys 2): 3351 assigned | 3345 processed | 81 I stole | 87 stolen from me -Node 3 (Phys 3): 3363 assigned | 3384 processed | 91 I stole | 70 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 335 chunks (2.5%) -================================================================= - -real 0m0.999s -user 0m12.130s -sys 0m10.549s - -CPU UTILIZATION: 22.701 / 28 - ------------------------------------------ - -(240): time { cat f2 | frun -s tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3389 assigned | 3398 processed | 104 I stole | 95 stolen from me -Node 1 (Phys 1): 3395 assigned | 3401 processed | 94 I stole | 88 stolen from me -Node 2 (Phys 2): 3358 assigned | 3354 processed | 91 I stole | 95 stolen from me -Node 3 (Phys 3): 3423 assigned | 3412 processed | 78 I stole | 89 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 367 chunks (2.7%) -================================================================= - -100000000 -real 0m0.994s -user 0m12.115s -sys 0m10.905s - -CPU UTILIZATION: 23.158 / 28 - ------------------------------------------ - -(241): time { frun -b 524288 : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (0.2%) -================================================================= - -real 0m0.373s -user 0m0.161s -sys 0m0.681s - -CPU UTILIZATION: 2.257 / 28 - ------------------------------------------ - -(242): time { frun -b 524288 : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3390 assigned | 3404 processed | 14 I stole | 0 stolen from me -Node 1 (Phys 1): 3395 assigned | 3392 processed | 2 I stole | 5 stolen from me -Node 2 (Phys 2): 3388 assigned | 3383 processed | 1 I stole | 6 stolen from me -Node 3 (Phys 3): 3392 assigned | 3386 processed | 0 I stole | 6 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 17 chunks (0.1%) -================================================================= - -real 0m0.487s -user 0m1.713s -sys 0m1.549s - -CPU UTILIZATION: 6.698 / 28 - ------------------------------------------ - -(244): time { cat f2 | frun -b 524288 : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3396 assigned | 3407 processed | 11 I stole | 0 stolen from me -Node 1 (Phys 1): 3393 assigned | 3390 processed | 0 I stole | 3 stolen from me -Node 2 (Phys 2): 3388 assigned | 3384 processed | 0 I stole | 4 stolen from me -Node 3 (Phys 3): 3388 assigned | 3384 processed | 0 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 11 chunks (0.1%) -================================================================= - -0 -real 0m0.506s -user 0m1.750s -sys 0m1.572s - -CPU UTILIZATION: 6.565 / 28 - ------------------------------------------ - -(245): time { frun -b 524288 cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.401s -user 0m0.646s -sys 0m1.429s - -CPU UTILIZATION: 5.174 / 28 - ------------------------------------------ - -(246): time { frun -b 524288 cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3378 assigned | 3378 processed | 12 I stole | 12 stolen from me -Node 1 (Phys 1): 3408 assigned | 3406 processed | 11 I stole | 13 stolen from me -Node 2 (Phys 2): 3393 assigned | 3389 processed | 5 I stole | 9 stolen from me -Node 3 (Phys 3): 3386 assigned | 3392 processed | 10 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 38 chunks (0.3%) -================================================================= - -real 0m0.724s -user 0m4.736s -sys 0m4.377s - -CPU UTILIZATION: 12.587 / 28 - ------------------------------------------ - -(248): time { cat f2 | frun -b 524288 cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3391 assigned | 3391 processed | 8 I stole | 8 stolen from me -Node 1 (Phys 1): 3402 assigned | 3402 processed | 8 I stole | 8 stolen from me -Node 2 (Phys 2): 3380 assigned | 3384 processed | 10 I stole | 6 stolen from me -Node 3 (Phys 3): 3392 assigned | 3388 processed | 4 I stole | 8 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 30 chunks (0.2%) -================================================================= - -100000000 -real 0m0.734s -user 0m4.837s -sys 0m4.740s - -CPU UTILIZATION: 13.047 / 28 - ------------------------------------------ - -(249): time { frun -b 524288 tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.388s -user 0m0.650s -sys 0m1.329s - -CPU UTILIZATION: 5.100 / 28 - ------------------------------------------ - -(250): time { frun -b 524288 tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3406 assigned | 3398 processed | 8 I stole | 16 stolen from me -Node 1 (Phys 1): 3381 assigned | 3386 processed | 13 I stole | 8 stolen from me -Node 2 (Phys 2): 3379 assigned | 3385 processed | 11 I stole | 5 stolen from me -Node 3 (Phys 3): 3399 assigned | 3396 processed | 7 I stole | 10 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 39 chunks (0.3%) -================================================================= - -real 0m0.699s -user 0m4.670s -sys 0m4.123s - -CPU UTILIZATION: 12.579 / 28 - ------------------------------------------ - -(252): time { cat f2 | frun -b 524288 tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3384 assigned | 3384 processed | 12 I stole | 12 stolen from me -Node 1 (Phys 1): 3383 assigned | 3391 processed | 16 I stole | 8 stolen from me -Node 2 (Phys 2): 3399 assigned | 3391 processed | 4 I stole | 12 stolen from me -Node 3 (Phys 3): 3399 assigned | 3399 processed | 8 I stole | 8 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 40 chunks (0.3%) -================================================================= - -100000000 -real 0m0.709s -user 0m4.779s -sys 0m4.523s - -CPU UTILIZATION: 13.119 / 28 - ------------------------------------------ - -(253): time { frun -b4096 -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 110 assigned | 110 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 100 assigned | 100 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.815s -user 0m14.345s -sys 0m5.676s - -CPU UTILIZATION: 24.565 / 28 - ------------------------------------------ - -(254): time { frun -b4096 -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3476 assigned | 3508 processed | 255 I stole | 223 stolen from me -Node 1 (Phys 1): 3383 assigned | 3406 processed | 218 I stole | 195 stolen from me -Node 2 (Phys 2): 3447 assigned | 3378 processed | 191 I stole | 260 stolen from me -Node 3 (Phys 3): 3259 assigned | 3273 processed | 208 I stole | 194 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 872 chunks (6.4%) -================================================================= - -real 0m1.041s -user 0m14.757s -sys 0m7.390s - -CPU UTILIZATION: 21.274 / 28 - ------------------------------------------ - -(256): time { cat f2 | frun -b4096 -s : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3419 assigned | 3417 processed | 264 I stole | 266 stolen from me -Node 1 (Phys 1): 3397 assigned | 3385 processed | 254 I stole | 266 stolen from me -Node 2 (Phys 2): 3403 assigned | 3409 processed | 246 I stole | 240 stolen from me -Node 3 (Phys 3): 3346 assigned | 3354 processed | 240 I stole | 232 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1004 chunks (7.4%) -================================================================= - -0 -real 0m1.023s -user 0m14.750s -sys 0m7.325s - -CPU UTILIZATION: 21.578 / 28 - ------------------------------------------ - -(257): time { frun -b4096 -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m5.732s -user 1m17.099s -sys 1m3.568s - -CPU UTILIZATION: 24.540 / 28 - ------------------------------------------ - -(258): time { frun -b4096 -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3398 assigned | 3400 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 3390 assigned | 3390 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 3394 assigned | 3393 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 3383 assigned | 3382 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.0%) -================================================================= - -real 0m5.739s -user 1m17.037s -sys 1m4.356s - -CPU UTILIZATION: 24.637 / 28 - ------------------------------------------ - -(260): time { cat f2 | frun -b4096 -s cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3403 assigned | 3402 processed | 1 I stole | 2 stolen from me -Node 1 (Phys 1): 3393 assigned | 3392 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 3391 assigned | 3391 processed | 2 I stole | 2 stolen from me -Node 3 (Phys 3): 3378 assigned | 3380 processed | 3 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 8 chunks (0.1%) -================================================================= - -100000000 -real 0m5.809s -user 1m17.489s -sys 1m5.803s - -CPU UTILIZATION: 24.667 / 28 - ------------------------------------------ - -(261): time { frun -b4096 -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m5.677s -user 1m16.787s -sys 1m2.697s - -CPU UTILIZATION: 24.570 / 28 - ------------------------------------------ - -(262): time { frun -b4096 -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3395 assigned | 3396 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 3401 assigned | 3402 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 3383 assigned | 3381 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 3386 assigned | 3386 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.0%) -================================================================= - -real 0m5.649s -user 1m16.588s -sys 1m2.467s - -CPU UTILIZATION: 24.615 / 28 - ------------------------------------------ - -(264): time { cat f2 | frun -b4096 -s tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 3398 assigned | 3397 processed | 2 I stole | 3 stolen from me -Node 1 (Phys 1): 3390 assigned | 3389 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 3392 assigned | 3393 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 3385 assigned | 3386 processed | 2 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 8 chunks (0.1%) -================================================================= - -100000000 -real 0m5.724s -user 1m17.252s -sys 1m3.823s - -CPU UTILIZATION: 24.646 / 28 - ------------------------------------------ - -(265): time { frun -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.160s -user 0m0.603s -sys 0m1.168s - -CPU UTILIZATION: 11.068 / 28 - ------------------------------------------ - -(266): time { frun -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 644 assigned | 649 processed | 7 I stole | 2 stolen from me -Node 1 (Phys 1): 640 assigned | 640 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 635 assigned | 631 processed | 0 I stole | 4 stolen from me -Node 3 (Phys 3): 643 assigned | 642 processed | 1 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 10 chunks (0.4%) -================================================================= - -real 0m0.221s -user 0m1.514s -sys 0m1.675s - -CPU UTILIZATION: 14.429 / 28 - ------------------------------------------ - -(268): time { cat f3 | frun -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 647 assigned | 650 processed | 4 I stole | 1 stolen from me -Node 1 (Phys 1): 651 assigned | 653 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 631 assigned | 627 processed | 0 I stole | 4 stolen from me -Node 3 (Phys 3): 633 assigned | 632 processed | 1 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 9 chunks (0.4%) -================================================================= - -0 -real 0m0.222s -user 0m1.524s -sys 0m1.621s - -CPU UTILIZATION: 14.166 / 28 - ------------------------------------------ - -(269): time { frun -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.168s -user 0m0.646s -sys 0m1.403s - -CPU UTILIZATION: 12.196 / 28 - ------------------------------------------ - -(270): time { frun -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 654 assigned | 663 processed | 9 I stole | 0 stolen from me -Node 1 (Phys 1): 643 assigned | 645 processed | 5 I stole | 3 stolen from me -Node 2 (Phys 2): 638 assigned | 637 processed | 2 I stole | 3 stolen from me -Node 3 (Phys 3): 627 assigned | 617 processed | 0 I stole | 10 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 16 chunks (0.6%) -================================================================= - -real 0m0.232s -user 0m1.570s -sys 0m1.926s - -CPU UTILIZATION: 15.068 / 28 - ------------------------------------------ - -(272): time { cat f3 | frun -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 652 assigned | 664 processed | 16 I stole | 4 stolen from me -Node 1 (Phys 1): 638 assigned | 638 processed | 6 I stole | 6 stolen from me -Node 2 (Phys 2): 633 assigned | 627 processed | 5 I stole | 11 stolen from me -Node 3 (Phys 3): 639 assigned | 633 processed | 5 I stole | 11 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 32 chunks (1.2%) -================================================================= - -3491 -real 0m0.236s -user 0m1.608s -sys 0m1.991s - -CPU UTILIZATION: 15.250 / 28 - ------------------------------------------ - -(273): time { frun -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.192s -user 0m1.117s -sys 0m1.442s - -CPU UTILIZATION: 13.328 / 28 - ------------------------------------------ - -(274): time { frun -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 649 assigned | 649 processed | 21 I stole | 21 stolen from me -Node 1 (Phys 1): 636 assigned | 640 processed | 19 I stole | 15 stolen from me -Node 2 (Phys 2): 623 assigned | 619 processed | 14 I stole | 18 stolen from me -Node 3 (Phys 3): 654 assigned | 654 processed | 15 I stole | 15 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 69 chunks (2.7%) -================================================================= - -real 0m0.252s -user 0m1.711s -sys 0m2.221s - -CPU UTILIZATION: 15.603 / 28 - ------------------------------------------ - -(276): time { cat f3 | frun -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 649 assigned | 644 processed | 11 I stole | 16 stolen from me -Node 1 (Phys 1): 644 assigned | 649 processed | 17 I stole | 12 stolen from me -Node 2 (Phys 2): 636 assigned | 645 processed | 20 I stole | 11 stolen from me -Node 3 (Phys 3): 633 assigned | 624 processed | 10 I stole | 19 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 58 chunks (2.3%) -================================================================= - -2113621 -real 0m0.244s -user 0m1.695s -sys 0m2.338s - -CPU UTILIZATION: 16.528 / 28 - ------------------------------------------ - -(277): time { frun -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.169s -user 0m0.557s -sys 0m1.117s - -CPU UTILIZATION: 9.905 / 28 - ------------------------------------------ - -(278): time { frun -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 645 assigned | 647 processed | 4 I stole | 2 stolen from me -Node 1 (Phys 1): 647 assigned | 648 processed | 4 I stole | 3 stolen from me -Node 2 (Phys 2): 643 assigned | 643 processed | 4 I stole | 4 stolen from me -Node 3 (Phys 3): 627 assigned | 624 processed | 1 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 13 chunks (0.5%) -================================================================= - -real 0m0.224s -user 0m1.455s -sys 0m1.679s - -CPU UTILIZATION: 13.991 / 28 - ------------------------------------------ - -(280): time { cat f3 | frun -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 657 assigned | 659 processed | 8 I stole | 6 stolen from me -Node 1 (Phys 1): 647 assigned | 659 processed | 12 I stole | 0 stolen from me -Node 2 (Phys 2): 641 assigned | 638 processed | 3 I stole | 6 stolen from me -Node 3 (Phys 3): 617 assigned | 606 processed | 1 I stole | 12 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 24 chunks (0.9%) -================================================================= - -0 -real 0m0.220s -user 0m1.544s -sys 0m1.582s - -CPU UTILIZATION: 14.209 / 28 - ------------------------------------------ - -(281): time { frun -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 24 assigned | 25 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 17 assigned | 17 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.167s -user 0m0.587s -sys 0m1.294s - -CPU UTILIZATION: 11.263 / 28 - ------------------------------------------ - -(282): time { frun -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 644 assigned | 647 processed | 7 I stole | 4 stolen from me -Node 1 (Phys 1): 646 assigned | 646 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 641 assigned | 643 processed | 5 I stole | 3 stolen from me -Node 3 (Phys 3): 631 assigned | 626 processed | 2 I stole | 7 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 15 chunks (0.6%) -================================================================= - -real 0m0.237s -user 0m1.556s -sys 0m1.917s - -CPU UTILIZATION: 14.654 / 28 - ------------------------------------------ - -(284): time { cat f3 | frun -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 661 assigned | 661 processed | 7 I stole | 7 stolen from me -Node 1 (Phys 1): 625 assigned | 622 processed | 5 I stole | 8 stolen from me -Node 2 (Phys 2): 642 assigned | 647 processed | 10 I stole | 5 stolen from me -Node 3 (Phys 3): 634 assigned | 632 processed | 4 I stole | 6 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 26 chunks (1.0%) -================================================================= - -3460 -real 0m0.237s -user 0m1.554s -sys 0m2.001s - -CPU UTILIZATION: 15.000 / 28 - ------------------------------------------ - -(285): time { frun -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 24 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 17 processed | 0 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (2.4%) -================================================================= - -real 0m0.176s -user 0m0.985s -sys 0m1.331s - -CPU UTILIZATION: 13.159 / 28 - ------------------------------------------ - -(286): time { frun -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 643 assigned | 645 processed | 10 I stole | 8 stolen from me -Node 1 (Phys 1): 626 assigned | 618 processed | 7 I stole | 15 stolen from me -Node 2 (Phys 2): 665 assigned | 669 processed | 19 I stole | 15 stolen from me -Node 3 (Phys 3): 628 assigned | 630 processed | 13 I stole | 11 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 49 chunks (1.9%) -================================================================= - -real 0m0.251s -user 0m1.742s -sys 0m2.164s - -CPU UTILIZATION: 15.561 / 28 - ------------------------------------------ - -(288): time { cat f3 | frun -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 655 assigned | 659 processed | 14 I stole | 10 stolen from me -Node 1 (Phys 1): 653 assigned | 660 processed | 16 I stole | 9 stolen from me -Node 2 (Phys 2): 639 assigned | 639 processed | 12 I stole | 12 stolen from me -Node 3 (Phys 3): 615 assigned | 604 processed | 6 I stole | 17 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 48 chunks (1.9%) -================================================================= - -2113621 -real 0m0.247s -user 0m1.810s -sys 0m2.194s - -CPU UTILIZATION: 16.210 / 28 - ------------------------------------------ - -(289): time { frun -k -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.163s -user 0m0.631s -sys 0m1.168s - -CPU UTILIZATION: 11.036 / 28 - ------------------------------------------ - -(290): time { frun -k -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 649 assigned | 652 processed | 5 I stole | 2 stolen from me -Node 1 (Phys 1): 655 assigned | 655 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 629 assigned | 627 processed | 3 I stole | 5 stolen from me -Node 3 (Phys 3): 629 assigned | 628 processed | 1 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 11 chunks (0.4%) -================================================================= - -real 0m0.220s -user 0m1.535s -sys 0m1.609s - -CPU UTILIZATION: 14.290 / 28 - ------------------------------------------ - -(292): time { cat f3 | frun -k -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 657 assigned | 661 processed | 7 I stole | 3 stolen from me -Node 1 (Phys 1): 656 assigned | 655 processed | 4 I stole | 5 stolen from me -Node 2 (Phys 2): 629 assigned | 627 processed | 3 I stole | 5 stolen from me -Node 3 (Phys 3): 620 assigned | 619 processed | 3 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 17 chunks (0.7%) -================================================================= - -0 -real 0m0.221s -user 0m1.521s -sys 0m1.649s - -CPU UTILIZATION: 14.343 / 28 - ------------------------------------------ - -(293): time { frun -k -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 19 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.169s -user 0m0.707s -sys 0m1.364s - -CPU UTILIZATION: 12.254 / 28 - ------------------------------------------ - -(294): time { frun -k -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 654 assigned | 658 processed | 5 I stole | 1 stolen from me -Node 1 (Phys 1): 641 assigned | 643 processed | 6 I stole | 4 stolen from me -Node 2 (Phys 2): 629 assigned | 621 processed | 3 I stole | 11 stolen from me -Node 3 (Phys 3): 638 assigned | 640 processed | 7 I stole | 5 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 21 chunks (0.8%) -================================================================= - -real 0m0.241s -user 0m1.573s -sys 0m1.930s - -CPU UTILIZATION: 14.535 / 28 - ------------------------------------------ - -(296): time { cat f3 | frun -k -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 667 assigned | 680 processed | 17 I stole | 4 stolen from me -Node 1 (Phys 1): 614 assigned | 604 processed | 2 I stole | 12 stolen from me -Node 2 (Phys 2): 646 assigned | 655 processed | 9 I stole | 0 stolen from me -Node 3 (Phys 3): 635 assigned | 623 processed | 2 I stole | 14 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 30 chunks (1.2%) -================================================================= - -3492 -real 0m0.237s -user 0m1.543s -sys 0m2.026s - -CPU UTILIZATION: 15.059 / 28 - ------------------------------------------ - -(297): time { frun -k -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 23 assigned | 22 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 20 assigned | 21 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.178s -user 0m1.074s -sys 0m1.427s - -CPU UTILIZATION: 14.050 / 28 - ------------------------------------------ - -(298): time { frun -k -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 643 assigned | 648 processed | 12 I stole | 7 stolen from me -Node 1 (Phys 1): 658 assigned | 652 processed | 9 I stole | 15 stolen from me -Node 2 (Phys 2): 624 assigned | 620 processed | 8 I stole | 12 stolen from me -Node 3 (Phys 3): 637 assigned | 642 processed | 17 I stole | 12 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 46 chunks (1.8%) -================================================================= - -real 0m0.251s -user 0m1.745s -sys 0m2.154s - -CPU UTILIZATION: 15.533 / 28 - ------------------------------------------ - -(300): time { cat f3 | frun -k -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 648 assigned | 649 processed | 10 I stole | 9 stolen from me -Node 1 (Phys 1): 644 assigned | 633 processed | 5 I stole | 16 stolen from me -Node 2 (Phys 2): 632 assigned | 639 processed | 15 I stole | 8 stolen from me -Node 3 (Phys 3): 638 assigned | 641 processed | 10 I stole | 7 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 40 chunks (1.6%) -================================================================= - -2113621 -real 0m0.243s -user 0m1.704s -sys 0m2.312s - -CPU UTILIZATION: 16.526 / 28 - ------------------------------------------ - -(301): time { frun -k -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.159s -user 0m0.583s -sys 0m1.086s - -CPU UTILIZATION: 10.496 / 28 - ------------------------------------------ - -(302): time { frun -k -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 663 assigned | 665 processed | 4 I stole | 2 stolen from me -Node 1 (Phys 1): 642 assigned | 640 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 626 assigned | 627 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 631 assigned | 630 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.2%) -================================================================= - -real 0m0.220s -user 0m1.523s -sys 0m1.631s - -CPU UTILIZATION: 14.336 / 28 - ------------------------------------------ - -(304): time { cat f3 | frun -k -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 647 assigned | 649 processed | 4 I stole | 2 stolen from me -Node 1 (Phys 1): 652 assigned | 649 processed | 1 I stole | 4 stolen from me -Node 2 (Phys 2): 632 assigned | 630 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 631 assigned | 634 processed | 5 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 11 chunks (0.4%) -================================================================= - -0 -real 0m0.221s -user 0m1.500s -sys 0m1.668s - -CPU UTILIZATION: 14.334 / 28 - ------------------------------------------ - -(305): time { frun -k -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.166s -user 0m0.593s -sys 0m1.288s - -CPU UTILIZATION: 11.331 / 28 - ------------------------------------------ - -(306): time { frun -k -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 642 assigned | 644 processed | 5 I stole | 3 stolen from me -Node 1 (Phys 1): 626 assigned | 630 processed | 6 I stole | 2 stolen from me -Node 2 (Phys 2): 659 assigned | 662 processed | 5 I stole | 2 stolen from me -Node 3 (Phys 3): 635 assigned | 626 processed | 0 I stole | 9 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 16 chunks (0.6%) -================================================================= - -real 0m0.237s -user 0m1.549s -sys 0m1.924s - -CPU UTILIZATION: 14.654 / 28 - ------------------------------------------ - -(308): time { cat f3 | frun -k -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 664 assigned | 671 processed | 10 I stole | 3 stolen from me -Node 1 (Phys 1): 664 assigned | 664 processed | 4 I stole | 4 stolen from me -Node 2 (Phys 2): 618 assigned | 613 processed | 0 I stole | 5 stolen from me -Node 3 (Phys 3): 616 assigned | 614 processed | 2 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 16 chunks (0.6%) -================================================================= - -3460 -real 0m0.234s -user 0m1.573s -sys 0m1.976s - -CPU UTILIZATION: 15.166 / 28 - ------------------------------------------ - -(309): time { frun -k -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.179s -user 0m1.011s -sys 0m1.357s - -CPU UTILIZATION: 13.229 / 28 - ------------------------------------------ - -(310): time { frun -k -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 674 assigned | 680 processed | 13 I stole | 7 stolen from me -Node 1 (Phys 1): 631 assigned | 636 processed | 16 I stole | 11 stolen from me -Node 2 (Phys 2): 640 assigned | 634 processed | 10 I stole | 16 stolen from me -Node 3 (Phys 3): 617 assigned | 612 processed | 7 I stole | 12 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 46 chunks (1.8%) -================================================================= - -real 0m0.251s -user 0m1.732s -sys 0m2.168s - -CPU UTILIZATION: 15.537 / 28 - ------------------------------------------ - -(312): time { cat f3 | frun -k -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 641 assigned | 638 processed | 12 I stole | 15 stolen from me -Node 1 (Phys 1): 635 assigned | 636 processed | 17 I stole | 16 stolen from me -Node 2 (Phys 2): 642 assigned | 643 processed | 13 I stole | 12 stolen from me -Node 3 (Phys 3): 644 assigned | 645 processed | 15 I stole | 14 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 57 chunks (2.2%) -================================================================= - -2113621 -real 0m0.248s -user 0m1.724s -sys 0m2.262s - -CPU UTILIZATION: 16.072 / 28 - ------------------------------------------ - -(313): time { frun -u -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.159s -user 0m0.587s -sys 0m1.126s - -CPU UTILIZATION: 10.773 / 28 - ------------------------------------------ - -(314): time { frun -u -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 652 assigned | 659 processed | 7 I stole | 0 stolen from me -Node 1 (Phys 1): 644 assigned | 638 processed | 1 I stole | 7 stolen from me -Node 2 (Phys 2): 637 assigned | 638 processed | 4 I stole | 3 stolen from me -Node 3 (Phys 3): 629 assigned | 627 processed | 1 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 13 chunks (0.5%) -================================================================= - -real 0m0.220s -user 0m1.476s -sys 0m1.576s - -CPU UTILIZATION: 13.872 / 28 - ------------------------------------------ - -(316): time { cat f3 | frun -u -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 652 assigned | 652 processed | 2 I stole | 2 stolen from me -Node 1 (Phys 1): 638 assigned | 633 processed | 1 I stole | 6 stolen from me -Node 2 (Phys 2): 659 assigned | 664 processed | 6 I stole | 1 stolen from me -Node 3 (Phys 3): 613 assigned | 613 processed | 2 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 11 chunks (0.4%) -================================================================= - -0 -real 0m0.225s -user 0m1.515s -sys 0m1.547s - -CPU UTILIZATION: 13.608 / 28 - ------------------------------------------ - -(317): time { frun -u -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (2.4%) -================================================================= - -real 0m0.163s -user 0m0.593s -sys 0m1.238s - -CPU UTILIZATION: 11.233 / 28 - ------------------------------------------ - -(318): time { frun -u -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 621 assigned | 616 processed | 1 I stole | 6 stolen from me -Node 1 (Phys 1): 648 assigned | 653 processed | 7 I stole | 2 stolen from me -Node 2 (Phys 2): 642 assigned | 640 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 651 assigned | 653 processed | 4 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 14 chunks (0.5%) -================================================================= - -real 0m0.228s -user 0m1.570s -sys 0m1.665s - -CPU UTILIZATION: 14.188 / 28 - ------------------------------------------ - -(320): time { cat f3 | frun -u -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 631 assigned | 635 processed | 8 I stole | 4 stolen from me -Node 1 (Phys 1): 655 assigned | 654 processed | 5 I stole | 6 stolen from me -Node 2 (Phys 2): 652 assigned | 649 processed | 4 I stole | 7 stolen from me -Node 3 (Phys 3): 624 assigned | 624 processed | 6 I stole | 6 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 23 chunks (0.9%) -================================================================= - -3494 -real 0m0.232s -user 0m1.520s -sys 0m1.937s - -CPU UTILIZATION: 14.900 / 28 - ------------------------------------------ - -(321): time { frun -u -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 21 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.173s -user 0m1.002s -sys 0m1.304s - -CPU UTILIZATION: 13.329 / 28 - ------------------------------------------ - -(322): time { frun -u -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 654 assigned | 662 processed | 14 I stole | 6 stolen from me -Node 1 (Phys 1): 626 assigned | 616 processed | 2 I stole | 12 stolen from me -Node 2 (Phys 2): 627 assigned | 626 processed | 8 I stole | 9 stolen from me -Node 3 (Phys 3): 655 assigned | 658 processed | 13 I stole | 10 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 37 chunks (1.4%) -================================================================= - -real 0m0.232s -user 0m1.645s -sys 0m2.021s - -CPU UTILIZATION: 15.801 / 28 - ------------------------------------------ - -(324): time { cat f3 | frun -u -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 646 assigned | 650 processed | 15 I stole | 11 stolen from me -Node 1 (Phys 1): 652 assigned | 660 processed | 16 I stole | 8 stolen from me -Node 2 (Phys 2): 627 assigned | 628 processed | 14 I stole | 13 stolen from me -Node 3 (Phys 3): 637 assigned | 624 processed | 8 I stole | 21 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 53 chunks (2.1%) -================================================================= - -2113621 -real 0m0.242s -user 0m1.770s -sys 0m2.068s - -CPU UTILIZATION: 15.859 / 28 - ------------------------------------------ - -(325): time { frun -u -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.159s -user 0m0.520s -sys 0m1.065s - -CPU UTILIZATION: 9.968 / 28 - ------------------------------------------ - -(326): time { frun -u -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 639 assigned | 640 processed | 3 I stole | 2 stolen from me -Node 1 (Phys 1): 646 assigned | 648 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 652 assigned | 650 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 625 assigned | 624 processed | 2 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 11 chunks (0.4%) -================================================================= - -real 0m0.217s -user 0m1.446s -sys 0m1.591s - -CPU UTILIZATION: 13.995 / 28 - ------------------------------------------ - -(328): time { cat f3 | frun -u -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 647 assigned | 654 processed | 7 I stole | 0 stolen from me -Node 1 (Phys 1): 648 assigned | 644 processed | 0 I stole | 4 stolen from me -Node 2 (Phys 2): 633 assigned | 632 processed | 1 I stole | 2 stolen from me -Node 3 (Phys 3): 634 assigned | 632 processed | 2 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 10 chunks (0.4%) -================================================================= - -0 -real 0m0.219s -user 0m1.451s -sys 0m1.598s - -CPU UTILIZATION: 13.922 / 28 - ------------------------------------------ - -(329): time { frun -u -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 24 assigned | 24 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (2.4%) -================================================================= - -real 0m0.161s -user 0m0.574s -sys 0m1.166s - -CPU UTILIZATION: 10.807 / 28 - ------------------------------------------ - -(330): time { frun -u -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 666 assigned | 666 processed | 4 I stole | 4 stolen from me -Node 1 (Phys 1): 639 assigned | 635 processed | 3 I stole | 7 stolen from me -Node 2 (Phys 2): 630 assigned | 631 processed | 4 I stole | 3 stolen from me -Node 3 (Phys 3): 627 assigned | 630 processed | 7 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 18 chunks (0.7%) -================================================================= - -real 0m0.221s -user 0m1.525s -sys 0m1.692s - -CPU UTILIZATION: 14.556 / 28 - ------------------------------------------ - -(332): time { cat f3 | frun -u -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 639 assigned | 649 processed | 13 I stole | 3 stolen from me -Node 1 (Phys 1): 661 assigned | 657 processed | 4 I stole | 8 stolen from me -Node 2 (Phys 2): 645 assigned | 645 processed | 5 I stole | 5 stolen from me -Node 3 (Phys 3): 617 assigned | 611 processed | 3 I stole | 9 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 25 chunks (1.0%) -================================================================= - -3459 -real 0m0.230s -user 0m1.447s -sys 0m1.981s - -CPU UTILIZATION: 14.904 / 28 - ------------------------------------------ - -(333): time { frun -u -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 19 assigned | 18 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.170s -user 0m0.994s -sys 0m1.184s - -CPU UTILIZATION: 12.811 / 28 - ------------------------------------------ - -(334): time { frun -u -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 649 assigned | 658 processed | 14 I stole | 5 stolen from me -Node 1 (Phys 1): 657 assigned | 656 processed | 10 I stole | 11 stolen from me -Node 2 (Phys 2): 643 assigned | 649 processed | 7 I stole | 1 stolen from me -Node 3 (Phys 3): 613 assigned | 599 processed | 0 I stole | 14 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 31 chunks (1.2%) -================================================================= - -real 0m0.234s -user 0m1.733s -sys 0m1.903s - -CPU UTILIZATION: 15.538 / 28 - ------------------------------------------ - -(336): time { cat f3 | frun -u -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 672 assigned | 678 processed | 14 I stole | 8 stolen from me -Node 1 (Phys 1): 639 assigned | 637 processed | 7 I stole | 9 stolen from me -Node 2 (Phys 2): 642 assigned | 641 processed | 12 I stole | 13 stolen from me -Node 3 (Phys 3): 609 assigned | 606 processed | 8 I stole | 11 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 41 chunks (1.6%) -================================================================= - -2113621 -real 0m0.237s -user 0m1.742s -sys 0m2.047s - -CPU UTILIZATION: 15.987 / 28 - ------------------------------------------ - -(337): time { frun -U -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.370s -user 0m7.105s -sys 0m0.401s - -CPU UTILIZATION: 20.286 / 28 - ------------------------------------------ - -(338): time { frun -U -X true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 649 assigned | 667 processed | 97 I stole | 79 stolen from me -Node 1 (Phys 1): 627 assigned | 628 processed | 87 I stole | 86 stolen from me -Node 2 (Phys 2): 647 assigned | 616 processed | 69 I stole | 100 stolen from me -Node 3 (Phys 3): 639 assigned | 651 processed | 95 I stole | 83 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 348 chunks (13.6%) -================================================================= - -real 0m0.351s -user 0m6.879s -sys 0m0.407s - -CPU UTILIZATION: 20.757 / 28 - ------------------------------------------ - -(340): time { cat f3 | frun -U -X true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 623 assigned | 648 processed | 112 I stole | 87 stolen from me -Node 1 (Phys 1): 659 assigned | 645 processed | 75 I stole | 89 stolen from me -Node 2 (Phys 2): 639 assigned | 639 processed | 75 I stole | 75 stolen from me -Node 3 (Phys 3): 641 assigned | 630 processed | 70 I stole | 81 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 332 chunks (13.0%) -================================================================= - -0 -real 0m0.356s -user 0m6.958s -sys 0m0.414s - -CPU UTILIZATION: 20.707 / 28 - ------------------------------------------ - -(341): time { frun -U -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.379s -user 0m7.594s -sys 0m0.538s - -CPU UTILIZATION: 21.456 / 28 - ------------------------------------------ - -(342): time { frun -U -X echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 642 assigned | 635 processed | 55 I stole | 62 stolen from me -Node 1 (Phys 1): 659 assigned | 661 processed | 61 I stole | 59 stolen from me -Node 2 (Phys 2): 655 assigned | 634 processed | 28 I stole | 49 stolen from me -Node 3 (Phys 3): 606 assigned | 632 processed | 69 I stole | 43 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 213 chunks (8.3%) -================================================================= - -real 0m0.366s -user 0m7.390s -sys 0m0.552s - -CPU UTILIZATION: 21.699 / 28 - ------------------------------------------ - -(344): time { cat f3 | frun -U -X echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 642 assigned | 601 processed | 88 I stole | 129 stolen from me -Node 1 (Phys 1): 662 assigned | 664 processed | 109 I stole | 107 stolen from me -Node 2 (Phys 2): 635 assigned | 652 processed | 96 I stole | 79 stolen from me -Node 3 (Phys 3): 623 assigned | 645 processed | 104 I stole | 82 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 397 chunks (15.5%) -================================================================= - -3488 -real 0m0.381s -user 0m7.262s -sys 0m0.612s - -CPU UTILIZATION: 20.666 / 28 - ------------------------------------------ - -(345): time { frun -U -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.459s -user 0m8.560s -sys 0m1.542s - -CPU UTILIZATION: 22.008 / 28 - ------------------------------------------ - -(346): time { frun -U -X printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 676 assigned | 655 processed | 34 I stole | 55 stolen from me -Node 1 (Phys 1): 677 assigned | 653 processed | 28 I stole | 52 stolen from me -Node 2 (Phys 2): 606 assigned | 631 processed | 48 I stole | 23 stolen from me -Node 3 (Phys 3): 603 assigned | 623 processed | 49 I stole | 29 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 159 chunks (6.2%) -================================================================= - -real 0m0.451s -user 0m8.381s -sys 0m1.588s - -CPU UTILIZATION: 22.104 / 28 - ------------------------------------------ - -(348): time { cat f3 | frun -U -X printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 656 assigned | 673 processed | 64 I stole | 47 stolen from me -Node 1 (Phys 1): 631 assigned | 655 processed | 68 I stole | 44 stolen from me -Node 2 (Phys 2): 651 assigned | 628 processed | 41 I stole | 64 stolen from me -Node 3 (Phys 3): 624 assigned | 606 processed | 50 I stole | 68 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 223 chunks (8.7%) -================================================================= - -2168851 -real 0m0.444s -user 0m8.384s -sys 0m1.634s - -CPU UTILIZATION: 22.563 / 28 - ------------------------------------------ - -(349): time { frun -U -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.389s -user 0m7.198s -sys 0m0.532s - -CPU UTILIZATION: 19.871 / 28 - ------------------------------------------ - -(350): time { frun -U -X -l 1:-1 true /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 639 assigned | 661 processed | 105 I stole | 83 stolen from me -Node 1 (Phys 1): 641 assigned | 648 processed | 84 I stole | 77 stolen from me -Node 2 (Phys 2): 666 assigned | 646 processed | 80 I stole | 100 stolen from me -Node 3 (Phys 3): 616 assigned | 607 processed | 82 I stole | 91 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 351 chunks (13.7%) -================================================================= - -real 0m0.365s -user 0m6.822s -sys 0m0.419s - -CPU UTILIZATION: 19.838 / 28 - ------------------------------------------ - -(352): time { cat f3 | frun -U -X -l 1:-1 true | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 648 assigned | 631 processed | 63 I stole | 80 stolen from me -Node 1 (Phys 1): 617 assigned | 637 processed | 89 I stole | 69 stolen from me -Node 2 (Phys 2): 642 assigned | 634 processed | 65 I stole | 73 stolen from me -Node 3 (Phys 3): 655 assigned | 660 processed | 56 I stole | 51 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 273 chunks (10.7%) -================================================================= - -0 -real 0m0.349s -user 0m6.948s -sys 0m0.408s - -CPU UTILIZATION: 21.077 / 28 - ------------------------------------------ - -(353): time { frun -U -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 21 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 19 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.420s -user 0m7.551s -sys 0m0.624s - -CPU UTILIZATION: 19.464 / 28 - ------------------------------------------ - -(354): time { frun -U -X -l 1:-1 echo /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 658 assigned | 659 processed | 79 I stole | 78 stolen from me -Node 1 (Phys 1): 665 assigned | 678 processed | 67 I stole | 54 stolen from me -Node 2 (Phys 2): 616 assigned | 619 processed | 70 I stole | 67 stolen from me -Node 3 (Phys 3): 623 assigned | 606 processed | 50 I stole | 67 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 266 chunks (10.4%) -================================================================= - -real 0m0.376s -user 0m7.422s -sys 0m0.510s - -CPU UTILIZATION: 21.095 / 28 - ------------------------------------------ - -(356): time { cat f3 | frun -U -X -l 1:-1 echo | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 635 assigned | 651 processed | 94 I stole | 78 stolen from me -Node 1 (Phys 1): 630 assigned | 625 processed | 69 I stole | 74 stolen from me -Node 2 (Phys 2): 665 assigned | 649 processed | 52 I stole | 68 stolen from me -Node 3 (Phys 3): 632 assigned | 637 processed | 79 I stole | 74 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 294 chunks (11.5%) -================================================================= - -3458 -real 0m0.369s -user 0m7.412s -sys 0m0.594s - -CPU UTILIZATION: 21.696 / 28 - ------------------------------------------ - -(357): time { frun -U -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.489s -user 0m8.475s -sys 0m1.648s - -CPU UTILIZATION: 20.701 / 28 - ------------------------------------------ - -(358): time { frun -U -X -l 1:-1 printf %s\n /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 675 assigned | 680 processed | 52 I stole | 47 stolen from me -Node 1 (Phys 1): 666 assigned | 661 processed | 39 I stole | 44 stolen from me -Node 2 (Phys 2): 606 assigned | 613 processed | 51 I stole | 44 stolen from me -Node 3 (Phys 3): 615 assigned | 608 processed | 26 I stole | 33 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 168 chunks (6.6%) -================================================================= - -real 0m0.448s -user 0m8.320s -sys 0m1.615s - -CPU UTILIZATION: 22.176 / 28 - ------------------------------------------ - -(360): time { cat f3 | frun -U -X -l 1:-1 printf %s\n | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 647 assigned | 663 processed | 49 I stole | 33 stolen from me -Node 1 (Phys 1): 633 assigned | 625 processed | 45 I stole | 53 stolen from me -Node 2 (Phys 2): 654 assigned | 651 processed | 39 I stole | 42 stolen from me -Node 3 (Phys 3): 628 assigned | 623 processed | 38 I stole | 43 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 171 chunks (6.7%) -================================================================= - -2168851 -real 0m0.446s -user 0m8.304s -sys 0m1.636s - -CPU UTILIZATION: 22.286 / 28 - ------------------------------------------ - -(361): time { frun -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.143s -user 0m0.191s -sys 0m0.322s - -CPU UTILIZATION: 3.587 / 28 - ------------------------------------------ - -(362): time { frun -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 654 assigned | 652 processed | 2 I stole | 4 stolen from me -Node 1 (Phys 1): 665 assigned | 677 processed | 12 I stole | 0 stolen from me -Node 2 (Phys 2): 640 assigned | 633 processed | 0 I stole | 7 stolen from me -Node 3 (Phys 3): 603 assigned | 600 processed | 0 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 14 chunks (0.5%) -================================================================= - -real 0m0.165s -user 0m0.497s -sys 0m0.558s - -CPU UTILIZATION: 6.393 / 28 - ------------------------------------------ - -(364): time { cat f3 | frun -s : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 660 assigned | 669 processed | 9 I stole | 0 stolen from me -Node 1 (Phys 1): 635 assigned | 631 processed | 0 I stole | 4 stolen from me -Node 2 (Phys 2): 657 assigned | 655 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 610 assigned | 607 processed | 0 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 9 chunks (0.4%) -================================================================= - -0 -real 0m0.165s -user 0m0.471s -sys 0m0.595s - -CPU UTILIZATION: 6.460 / 28 - ------------------------------------------ - -(365): time { frun -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.159s -user 0m0.712s -sys 0m0.912s - -CPU UTILIZATION: 10.213 / 28 - ------------------------------------------ - -(366): time { frun -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 654 assigned | 655 processed | 7 I stole | 6 stolen from me -Node 1 (Phys 1): 646 assigned | 653 processed | 8 I stole | 1 stolen from me -Node 2 (Phys 2): 630 assigned | 624 processed | 1 I stole | 7 stolen from me -Node 3 (Phys 3): 632 assigned | 630 processed | 3 I stole | 5 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 19 chunks (0.7%) -================================================================= - -real 0m0.223s -user 0m1.620s -sys 0m1.524s - -CPU UTILIZATION: 14.098 / 28 - ------------------------------------------ - -(368): time { cat f3 | frun -s cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 638 assigned | 642 processed | 7 I stole | 3 stolen from me -Node 1 (Phys 1): 629 assigned | 624 processed | 1 I stole | 6 stolen from me -Node 2 (Phys 2): 652 assigned | 654 processed | 4 I stole | 2 stolen from me -Node 3 (Phys 3): 643 assigned | 642 processed | 1 I stole | 2 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 13 chunks (0.5%) -================================================================= - -2113621 -real 0m0.225s -user 0m1.584s -sys 0m1.691s - -CPU UTILIZATION: 14.555 / 28 - ------------------------------------------ - -(369): time { frun -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.157s -user 0m0.700s -sys 0m0.866s - -CPU UTILIZATION: 9.974 / 28 - ------------------------------------------ - -(370): time { frun -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 644 assigned | 649 processed | 5 I stole | 0 stolen from me -Node 1 (Phys 1): 660 assigned | 659 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 644 assigned | 649 processed | 6 I stole | 1 stolen from me -Node 3 (Phys 3): 614 assigned | 605 processed | 0 I stole | 9 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 13 chunks (0.5%) -================================================================= - -real 0m0.228s -user 0m1.529s -sys 0m1.533s - -CPU UTILIZATION: 13.429 / 28 - ------------------------------------------ - -(372): time { cat f3 | frun -s tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 662 assigned | 665 processed | 6 I stole | 3 stolen from me -Node 1 (Phys 1): 650 assigned | 647 processed | 2 I stole | 5 stolen from me -Node 2 (Phys 2): 618 assigned | 616 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 632 assigned | 634 processed | 5 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 14 chunks (0.5%) -================================================================= - -2113621 -real 0m0.227s -user 0m1.556s -sys 0m1.621s - -CPU UTILIZATION: 13.995 / 28 - ------------------------------------------ - -(373): time { frun -b 524288 : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 21 processed | 1 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 1 chunks (1.2%) -================================================================= - -real 0m0.138s -user 0m0.058s -sys 0m0.192s - -CPU UTILIZATION: 1.811 / 28 - ------------------------------------------ - -(374): time { frun -b 524288 : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 644 assigned | 649 processed | 7 I stole | 2 stolen from me -Node 1 (Phys 1): 642 assigned | 644 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 639 assigned | 635 processed | 1 I stole | 5 stolen from me -Node 3 (Phys 3): 637 assigned | 634 processed | 1 I stole | 4 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 13 chunks (0.5%) -================================================================= - -real 0m0.155s -user 0m0.345s -sys 0m0.376s - -CPU UTILIZATION: 4.651 / 28 - ------------------------------------------ - -(376): time { cat f3 | frun -b 524288 : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 643 assigned | 659 processed | 16 I stole | 0 stolen from me -Node 1 (Phys 1): 641 assigned | 635 processed | 1 I stole | 7 stolen from me -Node 2 (Phys 2): 640 assigned | 635 processed | 1 I stole | 6 stolen from me -Node 3 (Phys 3): 638 assigned | 633 processed | 0 I stole | 5 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 18 chunks (0.7%) -================================================================= - -0 -real 0m0.157s -user 0m0.364s -sys 0m0.363s - -CPU UTILIZATION: 4.630 / 28 - ------------------------------------------ - -(377): time { frun -b 524288 cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.141s -user 0m0.139s -sys 0m0.325s - -CPU UTILIZATION: 3.290 / 28 - ------------------------------------------ - -(378): time { frun -b 524288 cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 638 assigned | 639 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 645 assigned | 644 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 640 assigned | 641 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 639 assigned | 638 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 2 chunks (0.1%) -================================================================= - -real 0m0.202s -user 0m0.939s -sys 0m0.905s - -CPU UTILIZATION: 9.128 / 28 - ------------------------------------------ - -(380): time { cat f3 | frun -b 524288 cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 632 assigned | 638 processed | 9 I stole | 3 stolen from me -Node 1 (Phys 1): 646 assigned | 644 processed | 4 I stole | 6 stolen from me -Node 2 (Phys 2): 648 assigned | 645 processed | 3 I stole | 6 stolen from me -Node 3 (Phys 3): 636 assigned | 635 processed | 4 I stole | 5 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 20 chunks (0.8%) -================================================================= - -2113621 -real 0m0.203s -user 0m0.959s -sys 0m0.954s - -CPU UTILIZATION: 9.423 / 28 - ------------------------------------------ - -(381): time { frun -b 524288 tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.139s -user 0m0.141s -sys 0m0.314s - -CPU UTILIZATION: 3.273 / 28 - ------------------------------------------ - -(382): time { frun -b 524288 tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 648 assigned | 649 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 643 assigned | 642 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 630 assigned | 633 processed | 3 I stole | 0 stolen from me -Node 3 (Phys 3): 641 assigned | 638 processed | 0 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 6 chunks (0.2%) -================================================================= - -real 0m0.197s -user 0m0.927s -sys 0m0.856s - -CPU UTILIZATION: 9.050 / 28 - ------------------------------------------ - -(384): time { cat f3 | frun -b 524288 tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 643 assigned | 645 processed | 5 I stole | 3 stolen from me -Node 1 (Phys 1): 644 assigned | 645 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 636 assigned | 635 processed | 2 I stole | 3 stolen from me -Node 3 (Phys 3): 639 assigned | 637 processed | 1 I stole | 3 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 10 chunks (0.4%) -================================================================= - -2113621 -real 0m0.200s -user 0m0.952s -sys 0m0.909s - -CPU UTILIZATION: 9.305 / 28 - ------------------------------------------ - -(385): time { frun -b4096 -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m0.222s -user 0m2.776s -sys 0m1.078s - -CPU UTILIZATION: 17.360 / 28 - ------------------------------------------ - -(386): time { frun -b4096 -s : /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 643 assigned | 627 processed | 29 I stole | 45 stolen from me -Node 1 (Phys 1): 677 assigned | 697 processed | 59 I stole | 39 stolen from me -Node 2 (Phys 2): 629 assigned | 622 processed | 27 I stole | 34 stolen from me -Node 3 (Phys 3): 613 assigned | 616 processed | 28 I stole | 25 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 143 chunks (5.6%) -================================================================= - -real 0m0.253s -user 0m2.835s -sys 0m1.388s - -CPU UTILIZATION: 16.691 / 28 - ------------------------------------------ - -(388): time { cat f3 | frun -b4096 -s : | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 629 assigned | 613 processed | 32 I stole | 48 stolen from me -Node 1 (Phys 1): 644 assigned | 659 processed | 47 I stole | 32 stolen from me -Node 2 (Phys 2): 627 assigned | 634 processed | 39 I stole | 32 stolen from me -Node 3 (Phys 3): 662 assigned | 656 processed | 34 I stole | 40 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 152 chunks (5.9%) -================================================================= - -0 -real 0m0.250s -user 0m2.865s -sys 0m1.331s - -CPU UTILIZATION: 16.784 / 28 - ------------------------------------------ - -(389): time { frun -b4096 -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.177s -user 0m14.678s -sys 0m11.938s - -CPU UTILIZATION: 22.613 / 28 - ------------------------------------------ - -(390): time { frun -b4096 -s cat /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 643 assigned | 643 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 642 assigned | 641 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 640 assigned | 641 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 637 assigned | 637 processed | 1 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 5 chunks (0.2%) -================================================================= - -real 0m1.156s -user 0m14.674s -sys 0m12.218s - -CPU UTILIZATION: 23.262 / 28 - ------------------------------------------ - -(392): time { cat f3 | frun -b4096 -s cat | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 644 assigned | 644 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 639 assigned | 639 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 639 assigned | 639 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 640 assigned | 640 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -2113621 -real 0m1.171s -user 0m14.701s -sys 0m12.480s - -CPU UTILIZATION: 23.211 / 28 - ------------------------------------------ - -(393): time { frun -b4096 -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.145s -user 0m14.541s -sys 0m11.772s - -CPU UTILIZATION: 22.980 / 28 - ------------------------------------------ - -(394): time { frun -b4096 -s tee /dev/null; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 644 assigned | 644 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 641 assigned | 641 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 641 assigned | 641 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 636 assigned | 636 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) -================================================================= - -real 0m1.144s -user 0m14.537s -sys 0m11.968s - -CPU UTILIZATION: 23.168 / 28 - ------------------------------------------ - -(396): time { cat f3 | frun -b4096 -s tee | wc -l; } - -================================================================= -NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 642 assigned | 644 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 641 assigned | 641 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 642 assigned | 641 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 637 assigned | 636 processed | 0 I stole | 1 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 3 chunks (0.1%) -================================================================= - -2113621 -real 0m1.154s -user 0m14.606s -sys 0m12.148s - -CPU UTILIZATION: 23.183 / 28 - ------------------------------------------ - - ------------------------------ -INPUT DATA STATS - - - -NAME: f1 -SIZE: 100000000 bytes -LINE COUNT: 100000000 lines - - -NAME: f2 -SIZE: 888888898 bytes -LINE COUNT: 100000000 lines - - -NAME: f3 -SIZE: 167808321 bytes -LINE COUNT: 2113621 lines - -total sys = 4367808 ms - -total user = 7381408 ms - -total real = 482860 ms - - -OVERALL CPU UTILIZATION: 24.332 / 28 - From 652e4b906299fa205e4a6505e95f6301ac78d0ff Mon Sep 17 00:00:00 2001 From: jkool702 Date: Mon, 25 May 2026 20:25:15 -0400 Subject: [PATCH 09/10] revert superscalar prefetch, keep do_lockfree_claim --- forkrun_ring.c | 374 ++++++++++++++++++++++++------------------------- 1 file changed, 186 insertions(+), 188 deletions(-) diff --git a/forkrun_ring.c b/forkrun_ring.c index ecdb4551..c5c96b2f 100644 --- a/forkrun_ring.c +++ b/forkrun_ring.c @@ -332,11 +332,12 @@ static inline char *try_simd_scan(char *p, char *safe_end, uint64_t target, __ATOMIC_RELAXED) #define PUBLISH_BATCH_SIZE(ptr, new_L) do { \ - int64_t _cur = atomic_load_relaxed(&(ptr)->signed_batch_size); \ - int64_t _abs = (_cur < 0) ? -_cur : _cur; \ + uint64_t _r_idx = atomic_load_relaxed(&(ptr)->read_idx); \ + uint16_t _cur_stride = (ptr)->stride_ring[_r_idx & RING_MASK] & STRIDE_MASK; \ + int64_t _abs = _cur_stride ? _cur_stride : 1; \ atomic_store_release(&(ptr)->batch_change_idx, local_scan_idx); \ atomic_store_release(&(ptr)->signed_batch_size, \ - ((int64_t)(new_L) > _abs * 2) ? -(int64_t)(new_L) : (int64_t)(new_L)); \ + ((int64_t)(new_L) >= _abs * 2) ? -(int64_t)(new_L) : (int64_t)(new_L)); \ } while(0) #ifndef GIT_HASH @@ -605,9 +606,72 @@ static int ring_is_spawnable_main(int argc, char **argv) { // --------------------------------------------------------- // ring_exec: Ultra-fast path for external binaries // --------------------------------------------------------- -// Note: ring_exec_main has been moved after do_lockfree_claim to resolve -// definition ordering (it references WorkerBatchState, EscrowPacket, -// prefetched_batch, have_prefetch, state, tl_drain_escrow, etc.). +static int ring_exec_main(int argc, char **argv) { + // Usage: ring_exec [fixed_args...] + if (argc < 5) return EXECUTION_FAILURE; + + int fd = atoi(argv[1]); + size_t length = (size_t)atoll(argv[2]); + char delim = argv[3][0]; + + int fixed_argc = argc - 4; + + // 1. Ensure baseline capacity for fixed arguments + if (tls_argv_cap < (size_t)(fixed_argc + 1024)) { + tls_argv_cap = fixed_argc + 1024; + char **new_argv = realloc(tls_argv, tls_argv_cap * sizeof(char *)); + if (!new_argv) return EXECUTION_FAILURE; + tls_argv = new_argv; + } + + // 2. Load fixed command and args directly from Bash's parsed argv + for (int i = 0; i < fixed_argc; i++) { + tls_argv[i] = argv[4 + i]; + } + + // 3. Tokenize batch directly into tls_argv + size_t batch_argc = 0; + int ret = do_tokenize(fd, length, tls_batch_offset, delim, NULL, fixed_argc, &batch_argc); + if (ret != EXECUTION_SUCCESS) return ret; + + // 4. Terminate argv array for execve + tls_argv[fixed_argc + batch_argc] = NULL; + + // 5. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) + sigset_t set, oset; + sigemptyset(&set); + sigaddset(&set, SIGCHLD); + sigprocmask(SIG_BLOCK, &set, &oset); + + // 6. Spawn the child (inherits FDs natively) + pid_t pid; + ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); + + // 7. Wait for the child synchronously + int status = 0; + if (ret == 0) { + while (waitpid(pid, &status, 0) == -1) { + if (errno != EINTR) { + ret = -1; // Mark the execution as failed! + break; + } + } + } + + // 8. Restore signal mask + sigprocmask(SIG_SETMASK, &oset, NULL); + + if (ret != 0) return EXECUTION_FAILURE; + + // Return exact status correctness (crucial for -E auto-retry) + if (WIFEXITED(status)) { + return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); + } + if (WIFSIGNALED(status)) { + return 128 + WTERMSIG(status); // Standard shell convention for fatal signals + } + return EXECUTION_FAILURE; +} // --------------------------------------------------------- // ring_exec_splice: Spawn binary and splice data to its stdin @@ -997,24 +1061,6 @@ static inline uint64_t fast_log2(uint64_t v) { // 2. TLS AND SHARED STATE // ============================================================================== -// ------------------------------------------------------------------ -// SUPERSCALAR PREFETCH STATE -// ------------------------------------------------------------------ -struct WorkerBatchState { - uint64_t idx; - uint64_t cnt; - uint32_t num_kills; - uint64_t offset; - uint64_t length; - uint32_t major; - uint32_t minor; -}; - -static __thread struct WorkerBatchState prefetched_batch; -static __thread bool have_prefetch = false; -static __thread bool prefetch_tokens_ready = false; -static __thread bool tl_drain_escrow = true; - static __thread int my_numa_node = -1; static __thread bool is_waiting_on_ring = false; static __thread off_t last_ack_offset = 0; @@ -1028,6 +1074,22 @@ static __thread uint32_t worker_last_num_kills = 0; static __thread uint64_t tl_remainder_idx = 0; static __thread uint64_t tl_remainder_cnt = 0; static __thread uint32_t tl_remainder_kills = 0; +static __thread bool tl_drain_escrow = true; + +// ------------------------------------------------------------------ +// WorkerBatchState: Pure value struct returned by do_lockfree_claim. +// Contains everything ring_claim_main needs to bind Bash variables, +// without any side-effects during the claim itself. +// ------------------------------------------------------------------ +struct WorkerBatchState { + uint64_t idx; + uint64_t cnt; + uint32_t num_kills; + uint64_t offset; + uint64_t length; + uint32_t major; + uint32_t minor; +}; static int *evfd_data_arr = NULL; static int *evfd_eof_arr = NULL; @@ -1175,6 +1237,7 @@ struct SharedState { uint64_t cfg_chunk_bytes; uint64_t cfg_line_max; int64_t cfg_timeout_us; + uint32_t speculative_max_claim; uint8_t mode_byte; uint8_t fixed_workers; uint8_t fixed_batch; @@ -1795,6 +1858,7 @@ static int ring_init_main(int argc, char **argv) { state[n].cfg_w_start = w_start_balanced; state[n].cfg_w_max = w_max_balanced; + state[n].speculative_max_claim = (w_max_balanced > 32) ? 32 : (uint32_t)w_max_balanced; state[n].mode_byte = byte_mode ? 1 : 0; state[n].numa_enabled = (global_num_nodes > 1) ? 1 : 0; state[n].exact_lines = parsed_exact_lines; @@ -3911,20 +3975,31 @@ static int ring_numa_scanner_main(int argc, char **argv) { // ------------------------------------------------------------------ // do_lockfree_claim: Pure side-effect-free batch claim helper. -// Populates `out` with batch metadata without touching Bash variables. -// Returns: 0=success, 1=no data now (non-blocking), 2=EOF, EXECUTION_FAILURE=error +// Populates `out` with batch metadata without touching any Bash +// variables. ring_claim_main is the only caller and handles all +// variable binding after the fact. +// +// Returns: +// 0 = success, `out` is populated +// 1 = no data available (non-blocking mode only) +// 2 = EOF — all data consumed, terminate worker +// EXECUTION_FAILURE = emergency abort or fatal error +// +// Precondition: my_numa_node must be initialized by the caller. // ------------------------------------------------------------------ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { + if (atomic_load_relaxed(&state[0].emergency_abort)) + return EXECUTION_FAILURE; + struct SharedState *local_state = &state[my_numa_node]; + uint64_t my_read_idx; uint64_t claim_count = 1; uint32_t current_kills = 0; int spin = 0; - if (atomic_load_relaxed(&state[0].emergency_abort)) - return EXECUTION_FAILURE; - - // TLS remainder fast-path + // TLS remainder fast-path: leftover from a prior boundary split that + // couldn't fit into the escrow pipe. if (tl_remainder_cnt > 0) { my_read_idx = tl_remainder_idx; claim_count = tl_remainder_cnt; @@ -3935,9 +4010,10 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { dlc_restart_loop: - // Escrow continuous drain: vacuums the pipe until it is empty, then snaps - // back to the lock-free fast path. tl_drain_escrow stays true as long as - // packets keep arriving; only set false on EAGAIN (pipe empty). + // Escrow continuous drain: vacuums the pipe completely before touching the + // lock-free ring. tl_drain_escrow stays true as long as packets keep + // arriving; only snaps false on EAGAIN (pipe empty). This enforces the + // Priority Inversion invariant more aggressively than the old one-shot flag. if (tl_drain_escrow && fd_escrow_r && fd_escrow_r[my_numa_node] >= 0) { struct EscrowPacket ep; ssize_t er; @@ -3951,7 +4027,7 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { // Do NOT clear tl_drain_escrow here — keep draining until pipe is empty. goto dlc_evaluate_claim; } else if (er < 0 && (errno == EAGAIN || errno == EWOULDBLOCK)) { - // Pipe is fully drained. Snap back to zero-overhead fast path. + // Pipe fully drained. Snap back to zero-overhead fast path. tl_drain_escrow = false; } } @@ -3968,12 +4044,19 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { uint64_t t_start = atomic_load_acquire(&local_state->tail_idx); if (t_start != 0 && r_curr >= t_start) { claim_count = 1; - if (sbatch < 0) { - int64_t abs_L = -sbatch; - atomic_store_relaxed(&local_state->signed_batch_size, abs_L); - } + int64_t abs_L = -sbatch; + atomic_store_relaxed(&local_state->signed_batch_size, abs_L); } else { - claim_count = 1; + uint32_t cur_stride = local_state->stride_ring[r_curr & RING_MASK] & STRIDE_MASK; + if (cur_stride == 0) cur_stride = 1; + + claim_count = (uint64_t)(-sbatch) / cur_stride; + + if (claim_count < 1) { + claim_count = 1; + } else if (claim_count > local_state->speculative_max_claim) { + claim_count = local_state->speculative_max_claim; + } } } @@ -4025,7 +4108,7 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { } } - // 3. Scanner finished check (EOF) + // 3. Scanner finished check (The 3 Sequential Conditions for EOF) if (atomic_load_acquire(&local_state->scanner_finished)) { if (atomic_load_acquire(&local_state->read_idx) < atomic_load_acquire(&local_state->write_idx)) { @@ -4037,10 +4120,11 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { continue; } } - return 2; // EOF + // All 3 physical conditions met in order. Consensus achieved. Terminate. + return 2; } - // Non-blocking mode: return immediately if no data + // Non-blocking mode: return immediately if no data is available now. if (!blocking) return 1; // 4. Spin @@ -4050,7 +4134,7 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { continue; } - // 5. Poll + // 5. Poll (3-way simultaneous: local data evfd, escrow pipe, EOF evfd) __atomic_fetch_add(&local_state->active_waiters, 1, __ATOMIC_SEQ_CST); is_waiting_on_ring = true; @@ -4075,18 +4159,19 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { return EXECUTION_FAILURE; } - bool data_fired = (pfds[0].revents & POLLIN) != 0; + bool data_fired = (pfds[0].revents & POLLIN) != 0; bool escrow_fired = (pfds[1].fd >= 0 && (pfds[1].revents & POLLIN) != 0); - bool eof_fired = (pfds[2].revents & POLLIN) != 0; + bool eof_fired = (pfds[2].revents & POLLIN) != 0; + // Strict priority: data > escrow > EOF if (data_fired) { uint64_t v; sys_read(pfds[0].fd, &v, 8); continue; } else if (escrow_fired) { - break; + break; // outer loop section 2 will read the packet } else if (eof_fired && !data_fired && !escrow_fired) { - break; + break; // outer loop section 3 will confirm EOF } } @@ -4170,9 +4255,26 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { dlc_check_boundaries: if (claim_count > 1) { uint64_t safe_count = claim_count; + uint64_t accumulated_lines = 0; + + // Get the logical target to calculate the overclaim threshold (1.5x) + int64_t sbatch = atomic_load_relaxed(&local_state->signed_batch_size); + uint64_t target = (sbatch < 0) ? (uint64_t)(-sbatch) : (uint64_t)sbatch; + uint64_t overclaim_threshold = (target * 3) / 2; + for (uint64_t i = 0; i < claim_count; i++) { - if (local_state->stride_ring[(my_read_idx + i) & RING_MASK] & - FLAG_CHUNK_BOUNDARY) { + uint16_t stride_val = local_state->stride_ring[(my_read_idx + i) & RING_MASK]; + accumulated_lines += (stride_val & STRIDE_MASK); + + // 1. Truncate if we hit a physical chunk boundary + if (stride_val & FLAG_CHUNK_BOUNDARY) { + safe_count = i + 1; + break; + } + + // 2. Truncate if we significantly overshot the logical line count + // (Ensure i > 0 so we always process at least 1 slot) + if (i > 0 && accumulated_lines > overclaim_threshold) { safe_count = i + 1; break; } @@ -4194,6 +4296,7 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { } else if (ew == sizeof(ep)) { uint64_t one = 1; sys_write(evfd_data_arr[my_numa_node], &one, 8); + // Signal the continuous drain to pick this up on the next claim. tl_drain_escrow = true; } @@ -4201,12 +4304,15 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { } } - // Populate output struct + // Populate output struct (no Bash variable side-effects below this line) uint64_t start = local_state->offset_ring[my_read_idx & RING_MASK]; - uint64_t end = local_state->end_ring[(my_read_idx + claim_count - 1) & RING_MASK]; + uint64_t end = local_state->end_ring[(my_read_idx + claim_count - 1) & RING_MASK]; + + // The number of ring slots claimed is ALWAYS the logical line/chunk count + __atomic_fetch_add(&local_state->total_lines_consumed, claim_count, __ATOMIC_SEQ_CST); - out->idx = my_read_idx; - out->cnt = claim_count; + out->idx = my_read_idx; + out->cnt = claim_count; out->num_kills = current_kills; out->offset = start; out->length = end - start; @@ -4223,125 +4329,20 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { out->minor = 0; } - __atomic_fetch_add(&local_state->total_lines_consumed, claim_count, __ATOMIC_SEQ_CST); - return 0; } -// --------------------------------------------------------- -// ring_exec: Ultra-fast path for external binaries -// --------------------------------------------------------- -// Superscalar prefetch pipeline: -// ring_claim → commits prefetched_batch to TLS globals (or blocks for N) -// ring_exec → (a) tokenizes N (or skips if pre-tokenized), -// (b) spawns child N, -// (c) non-blocking claims N+1 while child runs, -// (d) pre-tokenizes N+1 (overwriting tls_argv safely), -// (e) waits for child N, -// (f) shadow-orphan-rescues N+1 if child N failed. -static int ring_exec_main(int argc, char **argv) { - if (argc < 5) return EXECUTION_FAILURE; - - int fd = atoi(argv[1]); - size_t length = (size_t)atoll(argv[2]); - char delim = argv[3][0]; - int fixed_argc = argc - 4; - - if (tls_argv_cap < (size_t)(fixed_argc + 1024)) { - tls_argv_cap = fixed_argc + 1024; - char **new_argv = realloc(tls_argv, tls_argv_cap * sizeof(char *)); - if (!new_argv) return EXECUTION_FAILURE; - tls_argv = new_argv; - } - - for (int i = 0; i < fixed_argc; i++) { - tls_argv[i] = argv[4 + i]; - } - - // 1. TOKENIZE BATCH N (If not already done by the prefetcher) - if (!prefetch_tokens_ready) { - size_t batch_argc = 0; - int tok = do_tokenize(fd, length, tls_batch_offset, delim, NULL, fixed_argc, &batch_argc); - if (tok != EXECUTION_SUCCESS) return tok; - tls_argv[fixed_argc + batch_argc] = NULL; - } else { - // Perfect cache hit — bypass tokenization entirely. - prefetch_tokens_ready = false; - } - - // 2. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) - sigset_t set, oset; - sigemptyset(&set); - sigaddset(&set, SIGCHLD); - sigprocmask(SIG_BLOCK, &set, &oset); - - // 3. SPAWN CHILD N (returns immediately; child runs concurrently) - pid_t pid; - int ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); - - // 4. THE LATENCY HIDING OVERLAP (Fetch N+1) - if (ret == 0 && state && !atomic_load_relaxed(&state[0].emergency_abort)) { - // Use non-blocking mode: if the ring is empty, gracefully fall back to zero overhead - if (do_lockfree_claim(&prefetched_batch, false) == 0) { - have_prefetch = true; - // Pre-tokenize N+1 directly into tls_argv. - // Safe because posix_spawnp already copied argv into the child's address space. - size_t next_argc = 0; - if (do_tokenize(fd, prefetched_batch.length, (off_t)prefetched_batch.offset, - delim, NULL, fixed_argc, &next_argc) == EXECUTION_SUCCESS) { - tls_argv[fixed_argc + next_argc] = NULL; - prefetch_tokens_ready = true; - } - } - } - - // 5. WAIT FOR CHILD N - int status = 0; - if (ret == 0) { - while (waitpid(pid, &status, 0) == -1) { - if (errno != EINTR) { ret = -1; break; } - } - } - - sigprocmask(SIG_SETMASK, &oset, NULL); - - // 6. THE SHADOW ORPHAN RESCUE - bool child_failed = (ret != 0) || - (WIFEXITED(status) && WEXITSTATUS(status) != 0) || - WIFSIGNALED(status); - - if (child_failed && have_prefetch) { - int node = (my_numa_node >= 0) ? my_numa_node : 0; - if (fd_escrow_w && fd_escrow_w[node] >= 0) { - struct EscrowPacket ep = { - .idx = prefetched_batch.idx, - .cnt = prefetched_batch.cnt, - .num_kills = 0 // Must be 0 for the orphaned batch! - }; - ssize_t ew; - do { - ew = write(fd_escrow_w[node], &ep, sizeof(ep)); - } while (ew < 0 && errno == EINTR); - if (ew == sizeof(ep)) { - uint64_t one = 1; - sys_write(evfd_data_arr[node], &one, 8); - tl_drain_escrow = true; - } - } - have_prefetch = false; - prefetch_tokens_ready = false; - } - - if (ret != 0) return EXECUTION_FAILURE; - if (WIFEXITED(status)) return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); - if (WIFSIGNALED(status)) return 128 + WTERMSIG(status); - return EXECUTION_FAILURE; -} - -// ring_claim: Superscalar-aware batch claim with prefetch consumption. -// If a prefetched batch is available from the previous ring_exec overlap, -// consumes it directly. Otherwise, calls do_lockfree_claim synchronously. -// All Bash variable bindings are centralized here. +// Workers Claiming Data (Inertial Particles): +// The fast path is a single lock-free `atomic_fetch_add` to claim a batch of +// records. There are NO CAS retry loops on the fast path. If a worker +// overshoots and claims records that haven't arrived yet (inertia), it +// processes the available ones and deposits the remainder into an escrow pipe +// for other idle workers to steal. Escrow is pure advisory capability; forward +// progress is guaranteed by strictly monotonic indices. +// +// This function is now a thin wrapper: do_lockfree_claim handles all ring +// physics, and this function handles NUMA init, the SIGPIPE shield, and all +// Bash variable bindings. static int ring_claim_main(int argc, char **argv) { const char *v_target = "REPLY"; @@ -4379,14 +4380,18 @@ static int ring_claim_main(int argc, char **argv) { // --- UNIVERSAL SIGPIPE / TEARDOWN SHIELD --- if (state) { + // 1. Did someone else pull the fire alarm? (e.g., ring_order, or Fallow dying) if (atomic_load_relaxed(&state[0].emergency_abort)) { return EXECUTION_FAILURE; } + // 2. Sentry duty: Check if stdout is broken (Crucial for -u realtime mode) + // We only poll every 64 claims to ensure absolute zero overhead on the fast path. static __thread int claim_calls = 0; if ((claim_calls++ & 63) == 0) { struct pollfd pfd_stdout = {.fd = 1, .events = POLLOUT}; if (poll(&pfd_stdout, 1, 0) > 0 && (pfd_stdout.revents & (POLLERR | POLLHUP))) { + // The downstream pipe was cut (e.g., head -n 5). Pull the fire alarm! pull_fire_alarm(); return EXECUTION_FAILURE; } @@ -4395,34 +4400,25 @@ static int ring_claim_main(int argc, char **argv) { // ------------------------------------------- struct WorkerBatchState batch; - int rc; - - if (have_prefetch) { - // Consume the prefetched batch from the previous ring_exec overlap - batch = prefetched_batch; - have_prefetch = false; - rc = 0; - } else { - // Synchronous blocking claim - rc = do_lockfree_claim(&batch, true); - } - + int rc = do_lockfree_claim(&batch, true); if (rc != 0) return rc; // --- Publish metadata to TLS globals --- - worker_last_idx = batch.idx; - worker_last_cnt = batch.cnt; + worker_last_idx = batch.idx; + worker_last_cnt = batch.cnt; worker_last_num_kills = batch.num_kills; - worker_last_major = batch.major; - worker_last_minor = batch.minor; - tls_batch_offset = (off_t)batch.offset; + worker_last_major = batch.major; + worker_last_minor = batch.minor; + tls_batch_offset = (off_t)batch.offset; // --- Bind the byte-length to the target Bash variable --- char buf[64]; u64toa(batch.length, buf); bind_var_or_array(v_target, buf, 0); - // --- Export escrow/poison metadata if this was a recycled batch --- + // --- Export retry/poison metadata only for recycled (escrow) batches --- + // For fresh batches (num_kills == 0) these variables retain their previous + // values; the Bash layer only inspects them after a non-zero retry count. if (batch.num_kills > 0) { snprintf(buf, sizeof(buf), "%u", batch.num_kills); bind_variable("RING_NUM_KILLS", buf, 0); @@ -4430,10 +4426,12 @@ static int ring_claim_main(int argc, char **argv) { u64toa(batch.idx, buf); bind_variable("RING_BATCH_IDX", buf, 0); - int limit = 3; + int limit = 3; // Default to 3 retries const char *s_lim = get_string_value("FORKRUN_RETRY_LIMIT"); if (s_lim) limit = atoi(s_lim); + // limit < 0 → infinite retries (never poison) + // limit >= 0 → poison when kill count reaches the limit if (limit >= 0 && batch.num_kills >= (uint32_t)limit) { bind_variable("RING_POISONED", "1", 0); } else { From 926f7a7d7bb341bdda2db9ca600cd349f3de9fd5 Mon Sep 17 00:00:00 2001 From: jkool702 <107448833+jkool702@users.noreply.github.com> Date: Tue, 26 May 2026 00:31:44 +0000 Subject: [PATCH 10/10] build: update embedded ring loadables --- frun.bash | 2 +- .../forkrun-libs/forkrun_ring.aarch64.so | Bin 137416 -> 137336 bytes .../forkrun-libs/forkrun_ring.ppc64le.so | Bin 202656 -> 202656 bytes .../forkrun-libs/forkrun_ring.riscv64.so | Bin 104032 -> 104032 bytes .../forkrun-libs/forkrun_ring.s390x.so | Bin 140840 -> 140840 bytes .../forkrun-libs/forkrun_ring.x86-64-v2.so | Bin 142152 -> 142120 bytes .../forkrun-libs/forkrun_ring.x86-64-v3.so | Bin 150344 -> 146216 bytes .../forkrun-libs/forkrun_ring.x86-64-v4.so | Bin 150344 -> 150312 bytes 8 files changed, 1 insertion(+), 1 deletion(-) diff --git a/frun.bash b/frun.bash index b744f883..20065352 100644 --- a/frun.bash +++ b/frun.bash @@ -1739,6 +1739,6 @@ unset "b64" # <@@@@@< _BASE64_START_ >@@@@@> # -declare -A b64=([aarch64]=$'0 137416\nmd5sum:35a780a180a5931ab79e8256baedbbe7\nsha256sum:f0b70453287b932c7455e1db9b8508244c30bc55cffa5ea9410dc03133572fd5\034\035\036H4sIAHR2D2oCA6ybe3xTdZbAf3lQ0tKW8lAyPiCAqxlUREQoziyEgrY+qbVIdddJ0zRtYvMiSV8yakDUzPiiDkplfQR3PrMFH9sdUcvoShB1u+Njan186rofzYD66WdkFEZw2xXaPb/k/JqTw72788cWLvee7z33nPM759x7f7+Q3nn5NVcYDQahfkziZZGThHDgvmqakbByYYF/Z4uzM7qThP5P6j1D3l6gdflvgbR1Iis7Thjz9lUzstqWmSLvOiNeF8brwqiv9kKFiXsLimbc+Hm1P0fk7824n4zHenEWo54Vh1eGcvWXsUZ53cDL2RN8vw39qr3ydz1cVyD++h/lrwb96cWZMom8vYGMc2am7kJUXrdOfPbZmyXlj1/tXHXozZs/Gb/qy6NFi7dJvbWw/R3qy5zGt8Wrasus03ZYjtkSycLQJvHwzUJsEaXxTZZplkevVPHJa/4etltY3D/DvRP39bC5YGvQGKMbtkbYPBrnmsmxF7Zb8dgPW4CcC8IWInIY9xtgi8AWhS3GbLfC1obH7bB1kHOduL8Nto14fDtsd/wVNbsT93HYNsG2mZ0fH9jyyLoD079Z3/lhW/MLuz4/8Mrvfjynce/U/S1zbLevmfrM7Z0PXvRIV0tn6asHVx8/882a49sfu/wecX7ZgfbnXiruuPuD78oXXt+56qHId7/etuWx9V+t/8Omoz+54ezdD236h5pZ8w/uaDmvsv/e9f/W8cZTi5///P21x1bcvm7p7o3zdxdfvfG9lbNmv/9E+ujZS594+b1H139rm7fhuQ+fvPCXw09ecmb72nUrfvNP82OPHv6/xmcShSL5Uy1uFdUmUx77EzTidA0bl5u0+T8btflRQ+5eoD+/0LEjaztd536yaT3HjNr2V+rE49YZ11k68RzXsXMFbPM0+Oc68S/Tsf8w2J+mwW/S0X9Ax/4LOuPaJbTzU6Sj/4QOf1onnh6d/LSZtP3eqqP/c51xnadT38d19H+tE/+1OjypE8+rOvrFOnkw6/CP9MarY3+nzrge07F/vo6dn+vof6ETT6WOnc06+Tfo3I87dOz/uUCb/6eO/hYdv3/QyY9TZ7yHdfSbdPgBnTxcrxPP+zr67TrxhHT0x3Wek4d09C/Ssf+YTj4bde7HL3TysFHHzu919F/V4aMF2s+3gI7+Dzr6B3T079LJw0md+B/RsfNnHf2bdPJ/gU7/X6sTj12Hr9OJ5z2deLp07DTo6D+jE39MR/8TnT45T8fvDJ374tlMHa2i25KdVyxCvndSlg8V5fMLUb+vMJ/PRf264nz+COr3M/uvmLO8qiSfP5+Jf4qwPZGdYcdxfl+K9hPM/pemLLdPzedvoF8v87sOeR2L/2K0b2f2SzHO/tJ83on63in5/ErUL2f6zajfzfQ3oP4Qy0MBxmll+X8a9TuY/gNov5zZP4S8g9l5F+1YmZ2dqG9hdn5A/T6Wn+OoX8Xs/zvWpY7V5Uc4rmGW/0+Rl7N6DaL9HmY/jvojTD+NcQ6zOH+BvIeNtwnt2Fk832P8I6yOtRhPP8vPHLTfzfTLkXsZX412RpidNRhPgsVzC9qxMDvC6WwOhILOaMwViTmdwnll7bXORk/E0+yLxjyR2mtX+0NBT62rwe/JntM+43R3uJxNvqDL77tNip5IJBhy+kNuV8wXCopoLOIOhEW0M+oOBZuk6PcEQc0XDbkXXwLOI7GQ3y/CEY+rcekS0Rr1ezxhEZYMkB/siAZfsNHpikRcnU6P3xPwBGMi4Am4vRERCnuCcJG8lpsUYV/YI5rcwZgfNMKhqK/DGQ272oMQq9/jdLlldFGnL+iL6Z91NTY2toYX/68Kbn8o6hFRX7MnEI51Rj0xeQwcj8KRkDvgirZQG2F9g40eCD/UKa+EjIpo2O9ze0S7yxcL+xpFNBiO+IKxJjl+aR+SH+sMe5wNMt8i6vZ6Gp3AXU1NclydmeRDmmS2wp2iSeaxzRXxZQpHsspYFPKYYwFXi8cZ9LRz3fx8t0K9mj0xKfiCzaDlb/Vkig4lFIEWaJtAWJY36PcFW0SgNRhwhUFqyAspGoP2i4im9ogvJqVIULZOINsF3J9oaPX5Y76gbLgQjBEMggN3VtnTBl3S1ChtZE83QZfH4DyE5As2heQJ+Cv8UY+nRV4WCndmCxFxBZvBtyfYKEU41ZRLeSaZUG93ixPGGvMFPJIGQm3QaBm/rpi8YkM0FIGmao1Fs8lTgboizW2ioyni8YhGv2xd2EU7A/BvNsZGP/aStzXWGGoPiqZYpDWIRqGsreEJU02hSAucc8pki0zGYfgyM63umIDmU4rZc54Oj1udJCDTW3lcZi8P+KLZJpXlyT8B/ZUHsHHzGFQ/GPRE8liwNeCCq5tBnRlshKgi2fOnXKBlye13+QJ5pB2ycoqSxxWExMk7iJ3SCCJTxfY85IJiUzkUaeQuZO/kDTtz7+ahTJ9pjjfPvScGt3BEK6SwtzOax6Hxmhqdbnj0xfIrE/Uw35lnYB6Rj8b8a05thTZPJOrLvB14KeBGyg/F72NplE/vPBCB+xHeMaHWGNwVp6T3lF7yRN0ROWam29gaCIOpaGuAjzimhV0NcBsq4pR3rKu1Ax5M8h0VbPNF4OXk9zW4F0ZDC5eKymuurFjtXLzwkksmDheX5w6X5RSW5A5zChcvExMfahszn+ia8eNtU4bwPyLvyERko5iUp2lGLTGhbzrFSm5fwPxkr56c59FMrpKr/P/fP9JigTBNzq0ZXuh6tEB+ml+CLJGRC4QV5Xsz8iQxH+U9GdksFqLcl5FNYjnK2zOyUayZjJ/34+fsJvwg31GR3ddxvho/72b8MOp7GVdyxxjjOI+KM67WOwnG1Xqhm3E1f0syrtYRPYyreWkf42pdk2JczfMHuH2MZ4hxtV5I8/FinMOMq/XIEcbVemeEjxe5GM/nah1nYVytK8sYV/NbK+NqXWljXK1H7IxPrCMYV/P8cm4H469iXK0fq3k8WJc6xtX6rp5xtY7zMq7WWWHG1fqog+cT6xhnXK07EpxjnrfyPKCdbsbVuinJuFon9jKu1tF9PH7MTz/PD8Y5wDnaGeJ9ovKJ/78xUZfe7OcAXsYTz+HnA4xXoX6C8XrkSW4HeQ/jSeQpxlPI+xkfQp5m3PIvWT7MuA155gNpmh/kFsarkdsY9yK3M96B3MF4D/IqxvuQ1zPej9zLuEXln/E06icYH0GeZNz2W8w/44uQpxivR97PeBh5mvEE8mHGu5GLSfm8F7mF8RRyG+MDyO2Mp5E7GB9BXsV44lnMP+OWFzD/jHegfpxxK+onGPeifpJxO+r3ML4IeYrxOuT93D7yNONx5MOMdyMXBSz/yC2Mp5DbGB9Gbmd8BLmD8bI9mH/GbcjrGXcg93L7z2D+Ga9G/QTjadRPMl6P+j2Mh5GnGE8g72e8G3ma5xP5MOMDyMVk1m8vYv4ZtyG3MV6F3M64F7mD8STyKsZTyOsZTyP3Ml6n8s/4EdRPMF72EuafcTvyHsarkacYDyPvZ3wr8jTjfciH+biQCwuLE7/fYmHcgdzGeBi5nfEE8nKL9nvTwXiPM8urGVfv4zodO17GO5CHGY9vw3pxjvYTFu33dTfnaD/JOcbfy7h63/dZtN/v/YxXo/0BHuctWF/G1fxg2KI9HxjhdUT7ojCfP3tXlpcxruYT1kLt+YOdcTvaX8S493GsO+Nq/lFVqD3fqGPcivbrGX/nEaw7jxPtdxRqz08SjPdi325l/Mi9WHfG1fymp1B7PtNXqD1vSTG+6GGsO+NqPjSkY2eY8RF8zx5hvOdmrHsR6yu0bynSni9ZGR9G+zbGUw9h3RlX863yIu35VRXjQ2i/mvH0A1h37hfte4u052MdjPereQvj79yDded+0X53kfb8rYfxPrTfy3g12k8xruZ//UXa870hnk+0n+b8bqw742q+OFKkPT9U61o+DyxjvB77x8a4ml/adeyUT9GeNzoYP3wn1p37Rft1Ona8U7TnmWHGyzD+OONq/prQsdPNeJ2axzJuuwPrzria7/ZN0Z7f9jNehfYHGO/ZgnVnXM2Ph6doz4dHGC9H+6KY3Rc3Yd0ZV/Npa7H2/NnOuB3tL2K8HuN3MK7m31XF2vPtOsatap3CeLId6864mq93FGvPzxOMW9D+VsbjmJ8k42p+31OsPZ/vK9aet6cYvwDtD/C8of0hHTvDxdrz/COMf9GGdS9h40L7lhJtO1bGB5DbGO+PYN0ZV+uN8hLt9UUV4ym0X824xYd15/po31uivR7pYLxHzdu5HS/WnecB7XeXaK9fehjfivZ7+XjRfopxtf7pL9Fe7wwx3oH204zb0f4Rbgftj5Ror4/U55ETHO2XMZ5uxrozrtZX9lLt9VR5qfa6ycF4D9qvZlytx+p07HgZr0Ie5nbQfpxxtX5LlGqv17oZX6TW0YwXo/1extV6r69Ue33Xz7gN7Q8w3tuAded5RvvDpdrrwRHGLWhfTGV1R/tljKv1pHWq9vrRzvjIbnwOMG5D+w7G1fqzaqr2erOO8WG0X8/tuLDu3C/a75iqvT7div+/YABeSL6X1kv4VML7Caffc3OM5/hFhPcQXkV4ivC1ed+Iy8ZpNKsjTBPhZsLLCKe/x2MlnP4+io3wyfR7h4RbCF9EeBHh5YRPoXkgvJjwKsJLCK8mvJTwOsJp/usJp98n9BJOvxcaJnwG4R2EzyQ8TvhphCcIP53wrYTPIrybcCvhScJ/RPuE8DNoHxJ+JuF9hJ9F+4rws2nfEj6b8AHC5xA+RDj9/mqa8LmEDxNOf9/hCOHzCR8h/Bza/oYc/xva/4SfS/uf8PNo/xNup/1P+I9p/xO+gPY/4efT/if8Atr/hF9I+5/whbT/CafPjTrCF9H+J/xi2v+EL6b9T/gltP8JX0L7n/BLaf8TvpT2P+HLaP8TXk77n/DltP8Jv4z2P+E/of1POP1VpRThf0v7n/AVtP8JX0n7n3AH7X/CV9H+J7yC9j/hq2n/E76G9r8xxy+n/U94Je1/wq+k/U/4VbT/Cb+a9j/h19D+J/xa2v+EX0f7n/Bq2v+EX0/7n/Aa2v+E30D7n/Ba2v+Er6P9T/iNtP8JX0/7n/A62v+E30T7n/Cbaf8jn6zmk6rPGZ/oZ8bjKs+mfK6eBVbG1TN6mNmxT0yztP0OMX1VSzvTV7UcYfqqV/oZV3OIlfNNH53cuG/XSZPoChvEtpMb9/fsA5YyOT/O3B9wDvjWaWOVo2UHV3bZjHM+nmMzfaQ2ONc7zegYLTOKzLmMXADyPCIXgVxB5FKQG4g8HeTNRD4d5KeJfAbIrxN5NsgHiTxP+jfk5HOlfyIvkP6JvFD6J/Ji6Z/IS6V/Il8m/RN5hfRP5Arp35iTr5D+iXyV9E/k66R/ItdI/0S+Ufon8s3SP5F/Jv0TuUH6N+XkJumfyLdK/0QOSv9Ejkj/RG6T/ol8m/RP5DukfyJvlv7NOfke6Z/Iv5T+ifyg9E/kh6V/Ij8q/RN5h/RP5CelfyI/Lf1Pysm/kf6JvFv6J/Lz0j+Rfyv9E/kl6Z/Iv5P+ifya9E/k16X/gpz8lvQ/IW+d9nvpn8jvSf9EHpT+ifyx9E/k/5D+ifyZ9E/kg9L/5Jz8lfRP5D9J/0T+Rvon8l+kfyJ/L/0T+b+lfyKPSf9ENq4C/5acXADyPCIXgVxB5FKQG4g8HeTNRD4d5KeJfAbIrxN5NsgHiTxP+i/MyedK/0ReIP0TeaH0T+TF0j+Rl0r/RL5M+ifyCumfyBXSf1FOvkL6J/JV0n9WPjh1364KgziyGraKI5Wj7uTKLofIPVMF+1HPZ2GMD8pndO34+HZYSvcKW9UH6lltE4bl8nntAJsiWTkK86E9FePjsySrB//CtqILrtk6F/Ywh/o6Ba/mVaA7t6py1AW6R0yG3QJi09KHNcTb807c+cGq4k33zT2x6lf7pW0Ze7pytCFzrXHi2mysr2XeJd9NEaNRsFFfccdyiGtZJra6ylF4b+7Jxnlx1xNj49uHYDw2Ea+pr1ix/LspjtGTG1+feP/IfDjPMX30KYyFvnPoNrb2tV3fQfzHwN8xk1gAa+yZd4FNmOnsnVMmNkC8tX80zdidNs1cYDTEB4U8Nz7+8jHwNbb29R41ZuNA5aixUOwZW/vqLlc0MVghDPfNhbi+nyFGT4+v6II3fs3xG8U2h0lcemy9YVe6MjGYNiT/sr/IsTc9R4zuNIglKXjPzRTxwdNA12YQe2Z4Y30vGEeWvlggpu0zGlo2QyxSZ9t0eHeNj7/YCn731Kzee0zqVJR07Slw7F1iHll6bP2qXd/PkPG9kYlvLR/PIdGVNs3IjOedsex4ZBxfQZ7WEF3XyXHUzY59P+oqXx+eGF8m87WMXDP3RP41e/CaT7Gfxtb+K+Rb7JY5WHKWmL4Tpuhz46aut0AvZRJLIK7dGZYq65L+DGLzYFpQbup6BTjkdjAJXI41DfUbW3sgM9b0rHjNt3Ae1rpH3zWI2uPgq9Yolu4zVhwVhuTgzofjO6S+vE5dI4/jRfEaKafHxmc5rPGaz9BG8dh47Wlw3bcQv6zhEHDok93yXMAkajO9+GHlqEk4RuthcxihbhCb6q9Ds8TopyfHtx+a5RiFOWRX1Gi8r/5+x4gD6gezy8GnjDO+vh9qss8ovpaxvQN+thlnvB3/5ucfQGrfFifW/GpU+jYnB/8L9tl+PTV/bRBX3Jyfvw3A/jj+0KDDlJ+/Fsxf3Cgu/dAklv0jyMdxTCUFuTHNhPHEYW5mM2fHtAvGYYAxxB90jESNhvviMAZowcF9MIbDRlGbq0X2vpA5vV/WcOTOD/g5Wae7McfPQZ3miDVHDcbkoGHrph1c90XIx07Ix1xx2ttzIR+yT2WNWvH6C6BGBqhRGrgB8vQZud/PhRytEo7lk2A/N23YsEo+u8yO5W75bIH70mx17DUYxKX7zGJDetZTZwjr5BvcmfvVvKDeKvZmnotwvTBmdeKQn30WuDcmidrPYR8vEbVbrikGH/GaLWbLYqM5WWP7adkNX50cv3SL3zIdVg4LDst4UmID9EattDVnD9wnk7JxrAS+3wzHFsfyTeasj2RJ1oejOOvDVQg+/Nbp8Ayv+USOHa5LgX2pu/OH8YwOxFebnvNkjUjui7w1SyzZIj/Oc8Rr3gX9VeZ4jQPik3qbJqMtYG/BOckMU+CZML4Jlmdbagxw/RZhKNonY35WbIB7slbGmwKdsamzR9LwvDZAL1QY4jVfbDf+D2t/Hh9Vdf8PwOfOHbIR1iyEBM0k4ELElYSAaHOTqKioaBir1bYk4IKm1iJaQdBMwFbsaGUEiwW/TQBbTdSKGoSpWgKo1aIVE3dtmUnC5rghS2ZC4D7v9zn3Zm5CsP09z/NHXpl77rln+ZzPfj7nc8buyhXB24EXHSvKxnItduUCnul1KwlfCa8hai6eQWounKvsf6ivYibgXJouYk54H00sixLmNmzITwib8GE133oL/iJBtZeXZLWX5Kt4FGPOA4woD+z130EYJbDOqOG/w/tQrq8iFN50B+RIihvrBbqquB/lxAVtqIg56wtNwZt8XLjqJfyqMI8w2gijjVrAaQzauNOCY57bhuOiHjjeJvtU63LTfrNIGPdXwI5Pr2WbSfUVEevbKt3+dknPtz+31jr3dbR9wPQagEOo0yz8E8rv/2nWcNBIwdX4XYu5+9DeG46+/pJk4YDHV3GZVV8M81WsddR5023V8fkqyu05aMSjPjAaWq/WaoyIPWbDyiNiN4GvEPfBVyXu/97GJ7TRJueytMIl5+JKkd+PErHf2N9nidguyLwwxyJqe+Z8L3mdb0kFYWyXjeL4zwMtDVP9/NtaRyHf020dqNhD2j/PuIrw5TdD+A3G1gaZzm9y7PeeRfJ9osUjzHLtfbPceP+oDvkPnnpohqvhEHA8P0U0deLb6M16QxS8CDK5ZZKob9mfKGLghRVdo0Vsiytjm65n+GcYxr5wuRYoW/pHyJYRBQ90myu6wE9DWnSD0MX6mt9rc04HTkVvLm/Yn2jEukYbsR2ujMhR3YiF9LrrpLyeUdaAsQQwlgDxf+aRuEx1Z029p8pNvuyruBjl/PZU0AX5ipQF+K4N/D2spzcS9z9G/x70PRcyhXxhuUv4ne/f43vTfPkStBXG92w3D32VoK8x6IvrdwbeETfXu7L9nG87fs+FHrKDMgjjhiwcbs+F8+pvDoTZm1JmvQqZ5ZIyC3Km4ADgacN5Bdq2xxbSMwqedozd12fsfF9vjT2bMhVjd2EcIegblGezMIcazMEHvaVmnMLlgzMSx07DN7sxDiVXMhs5Tls3Yhnm8qizrLd++LcGNe6ExrxE0dR1u7vhHsiS9ld+9WKJ0CNtA7iuesO12yd/yHlBESigPqhdVhoTldDZRclHabrw2/NdlCACh/UBBVUJRqxTdzeK6sroDKFFktAOZawm0vyzXJn+RZB5IX1kwYHDwANXdEMIMhgw8VNfeBu40LcPfsO2+B3b4Lc78a1x1HyZ623jkoCs5Fy5ZsSFrtsvaFC60Jty7hdBv94hBNe3wlleW2YEwmeKmIdtHTWbwmdC30kQDa2AK8c0GzDvO6Z0jOcPrjR/3a3jJ9a5MiOLMO5rBoimkZhnInhgjUtMuhPwmJQoAlsOE6/TIw1Ysy2u9G1hPbsAOmTjPPTXhv/E87A+EjgwolHH2MYfNddDN5kkILszoHMFXWrM9tw4r+0YG79pk7ijvmNfT6Gv/XjHcezDf37Db+3vtpBH1RjL+P4w+k1LEoERC+9t7Ts/0La/yjXSL5KMWC7WsAz4qon7W9w+X0sl4OiG3qN9tVB+57K+M/CdC9+1AZZGqhG7IEnEtmE8lfvNpjbAFDI/5pz/xG6bRsV3fdugjgQ7rAlydxLnVYr2CmcXR9Oho3XmiwDhObvL9G7EfAir5kNmIdvpO4e5+kg/vxf4Pn3e+OizTnsJ8vDyocJrLh4qeaTHbcQg/yuyiQdDosXhxSLgwnzJF2HHBJNQzrUKQQ9owLywxvueg8wMLTYm1SSIfaxfCb0m9yHoFCifmSDen3Ge2HfLYOGd9c3CR4VDd+ZfB9oShgjkC+GfIXacZ67yXGE+temXbfpNf1qUCt4KezQMnK5x6ZHKFOH1zJ41sXKgKKwEDNB35N1kllVObE5BWZIqO90q87AsVZU9nKTKfMkoG6rKvk5UZSHI0sp0VXa5VWawLEuVPZegyuoTUTZKlQ2yygTLPKrstgGqDHRTWDnGGp/bGt8AlJ1qjc8q87BsnDU+3RofZHblWdb4XNb4IIcrC63xWWXU+dG7Gp9mjc8lCmedxzI9MkhTsALuzJFyKLEum/wc6yx5N3+TP/CdXcZn/m97wJg0437w1+9NL+tJugPOtIOf1ZN2TLMQdVtAby2riUupYs4voHfb3x+d9qS0uTsoC8BbqUtSpySPrARf7JgsghOAO4ew9pUpEt+kvvlhl7JTLgKv7YvHW4AfHZONYG2SuMpILW04aaGxbBNw4y3on79JFVfdMBN4inae+u7eVid+1c6eGWVbSVZbQiv5CIaXv2p2frQM6zZrsBGbIRIjm4lj806KhhZrgcUYR/0AURS62Qi6oBeGoT+VYbyhrVpgKP6HZ6Ecc+XzUtQNox5/f4rfIX1A4CX8p57K3z9lffxv03XpI/gp3t2APttQv1wT22fBDgvN1QK1sMVuxB9hOuSwtEELQuhne5fq92X8b4I+xTFtw2+zWgTDaJNzpu5/UZfyk9hy+ui0LyRfl3Y0YHsr3ncS3sOBC8Uitn+tFigCX+X/BNRpQ7tPuhK2KV9IZsEAtMWxQP+PLcC30PtjoQHRDW8CdpVShmREZgFmYfBdtl/BcbINa2z0G4w9HJdLpaCN0AwjyPYJu3PwDrzn7JBsIz6PdMKz2gh6ssQdHtAE7NFhsLGG5Y0qXVYCXP46anr/AZy7EHw1pOuNeeDbbav0ho5pIjgH37atKm+g3tAxzQj6Os0m8tt5qJ9gjYXzkOMB33wP5Z5RWXfknXcxUKI2+wUpT+Jj2RczVzyDMlMf8T7aLFgjxLqykA7d2NeCvgPkl0lyzVGG+u/ity81Wnzwc+iZeqLkmyzf3ypo0xdQNynk/PC/rYZtpBU0dSl/A39fjd914Keng88BNtP261MmHdS1wKFc+q4yGydgXJvuE89tuk/Dnwt/+nMvgf/M7aIfxYgR5sshbw+g/jLIg1bwobkn1rR6Zs+dZ5gzJlDe0HdDWvsx+wUsyMs70DflB+1A8Bpv5X3GMpt+tOUXtW7Nb16Z2z1kztOg8TzQ15pbq6JlQm9cc2teVIAP1wlR/U+sI/useVHMuSHbuMegzY/vawqgk8CGdY7LrpNnmt6XgNPLBkBnpQxDHXt89JmdjjFKHoJxgs9V0w9Ae61Nz2jUhvpaSE/noc7+VqPh4OfQZcjL9BGKv1ll1GO7aE9A3zf15PePThM9/hXAtrFqoK9isrUG4O9N9KPcjHWvhC4mvpsxMfdObU4YvJ5614xufV9Sgu0vhE6eJmIXo25bmhGrTaBPTGsMjxCxMN6VzM6feDXepbnF+zVH9X0X03YcYWAdB0hdnmsxCe+pO7GtMvw2oDtppxrBUvdZxZtdQyeYgMG1XUreEiaW360RsAjuYr+55F3pEegf3jJhTMqHrlTlgp6/BLJX+jVFI2HF9qkbHcE3R6cZUh8ELCScwvJ9mvSXkS75nu/+GSO/z5C6Fefjxjvi53eEJZ5/ibbqu8z1X/X4/V5poM+G9CB9Z+j/6LQ3JA+qZxgA7WGfO+BW8yloFtEJJwBfPV0O3yVhtFX5Ltt0X8vXMWUDgEdsYFn7EBF7iGVDjNhW6EUh1A2vVfiSO3v0RA3vCGPYOpPy5mUPz4MeXzIO6weZKT74davvsLmefqkdMTXGh7kFDXy2x8nxf2K9g03thf3e8p6cb1oB58tvt9vvgYsH8K6kUJujPfuLVvDelZ4jZtPWPr5o2hdcP8JAGAMCHD/4Gli5MakEdv9mjs1tTKKvrnTokgoJq6T6O0T9gIDrLF/FxpjUDwtgM03o9d5IkO/XWe9D7mgx/QW2Pi/7Cw0I/Irj1uL91WqqP9BnEfF4C+VYvq/ln3Y7R8wJzvGzTplVZ7NVp7nbnPBizFq3axUvtfk6622w6vliZjH9wqsxlrzKhEAIumF+qtHQNsTVkAedOpwjYh9ErTYFxo/3YeiYz/N76Jfv2N829/l2KOTIeBF8w/oWNtCEzdIOXd/A+pYd2ujxJEq+TL3jJsIdMDpEfgK8Ia+sjTn82vT7SDsis6BtiK/lipil50rcyyz4Bn2Nh7wkvdaf/lAFdID5kEfV9dB1bf2GtFkZJS/2VXTaa96cGJgSk7pOQXNSdEIPLRhJgVKrPJQcLbbH9NOY5OXSVg8n9R7T2D5jeht9wXZpYr/2GDi+kqiS9b4rX20Rv3v3++Ynvv3ehJ74NHhXT/8iOZBnjwu0eAb6Pt8BD21A775T+vTdSHi4FTyc/XvYN/rqzK9bucEVtzOVTrJN4uZoRz9VWu9+vov27mcpn7vN9S9KOswseAjPz1u/H4yyHd/wvu37UiDL6AveDxrG+6jEjdcauFfzY+iCrYt+FCCOVBbAxgVtVKUYQV08VNFm+lv0wvo7oPN9n5e0dlVe052PvoU+drQkxiDHYvyu8gwj1pyovqmFrk4fSNOh+1rF7Ds3GsDhG1CfOi33seyyGSw7p3fZdSyb0Lvsapad27vsSpb9qHfZVJSx//WQORxPicio3gMZy/EttPqvOUPEqKfNw3NNijX2cwxZNpdl51hlE1TZL1k2wSrDGG7l87loA33fzN8/ErGP8K65TNWfSbiUidh0wPPOskEBwDzow9jGWGviSxHByopyWZZrlVVW6MG5qAsbQJaPtMsTRFDRSnIgC2Xyt0gJZOA397nqJU1DlkN/5x7OkGicx6ZevKjFnDVuG+U619T2PSm/nihQ7aYE6NfpPk3ExqHNZlecH4ZOE17JY8TAwAlRySuLYHNvz7thSox2g9v3o8BJ9GG5QN/jRWy0UOOhXi08AwO/WSKC4/EdaZf1WUfgm1yUh8YbsRz8rnlEBGvKXZMWlkP3TIS9fbLwZg4UV/nKRGCDEEsfgy2fedkEf+eigYFJ6IshretRtsmVGQnBHn3JBV4JPXumJnXGxrpOuedWVHWGMUnujaL9+Wg/D7pU5Rki4OTfJeuUTqeNMibCVitaKMgvRjV+jzbmPmIEK++7r7UavyvLRaybdDdeNK3mnhDs0tBoLdZ62Cyk3yoMnYA0no66vgXjN4ZGl8YkDNF+FdrxgY7nAh85xxKRVr3kqNKv+S4POnwVxsgx1B42i3bI/S4RYH32YX+zp9v02vOugp5P+BGW+kNGcO0oUfhqLdbNDRgsdgegiy8tax4YOBXjCeO5nqFc5GuhgYFVKOO3afh2Pmj8pt8bwfmniybQRXAHU2YOveie0nHCWwL9nTwAfOtR2BiQFSLWBf3Mi/W34bcMOMy1PdQZ51lhqVtlN9p7rFvVemyoP2qufwz4/RL64Td7f+Cblx3fLMc3yxLUN184vsnTen/T4PjGHp+cJ9YnE38jMP+RmLMHMBdjROGos5a05BhLWtKoZ5E3Y34e6Mh5k2nTp/mFuDiQK06Ve/yFs3+98UBOdAK/1cRDLZ0JYphWWP/9R8O5p6n5c8WI6lvyYOMPVPSfjvp3Dkf9M+PPB9LwPN7xPgPPxY73mXjWVd+51ljUOFyB3s/uPs+j+tTP6Xm+ZO6SFlWWzLJJLEu50i5L6ak3cI5dNrCnLDVgl6X2lJ3e096gnvZ+2VM2uKdsyB122ZCeb4f21BvaU2/YOrtsWE+94S/YZcN7ytJftMvSe8oyXrLLMnrKsirtsiyWBVl2os8uO7GnTFtql2k9Za5ldpmrpz39V6pME7pf+GbGiCPuR5e02LB2DTVAF25/mbh6UtvXZpFYour8kjJ4PHVt6vU/CmgPiaDNWz4/BB4BfLsa/8OsQ5w0wBeHiabRoGWOZ7DcyzUmrf7ALAQ+y7YyUI80kOOgAe1r06IBFW+w55CiAeMrs6me8RTAq6jZ+/uBju9rI72//8T6vvlLfH9G/98fPuTo/8ve379l978X35/T//cRx/e1e3p/v9Hufze+n9D7+yzr+8+d37fz+2QVb+HztTxtf99mNonJ8e/pV40dVLqT4ec64JsS+kjSGu/GN6FZ7sB4UV/xDurUPyYK28FTFm1JD+wvAa4kKbny4UHq00qPJz8VnozAxYcUL2UdyXN9GQF9+xTZ7qzHZ8beOijl9VJ+J+oz6DupmCzH76voPg00Bvls25xO3z1ktt+yU5YKIzXw+4PKf0W/fSZ0sRB0MQE9LBP62ADMDfbn8I/Ey6tGu30VM6X+CnvkX3c+ehP0jGWHrPgGt3jB8yvh7cB49fQLAlvwnrpuJXS39S5XYPH2xNgHB+XYHq2HbuoZc3+FcNffUZktgpTLt90uvBmWXB6FOi9jbJTPG/G3HHKpSx9V8NGaQYHOtkGBrNGDAxmXFfm5t2ZeI2LmBsj7bRiLlNWZ1IclTJvQXyhZFFJ+85ky/HmUGZeyLEuWbUFZI+ePMugiS1mWVzk4QHx50qrbU14/OJCP8j/1rR8aHFiE8sc5P2e5Z4hs51HWn+Vsf4hs5yGO7xJn+0NkO79l/Xuc7at2fFzvec72h1IvaLkH5ZULnO0PlfXvZLmznfqhgTUo/yXKffc52x8agC3aMpv9LhBF87NFgHrQzAIhbbjfgqa5BnWujEj4QFw3SMoygjMSxdme64W3q0wUCS1xeNr8xOFJN/6klfIw9JTSwxiMw3b2zBXBbHxXv0gPvGyt7fQcEWw5pOw26QfCuxM71TP3h5q3DA3803p/0HrOpN6hjyigD1ts1QNb8H633MMaUcDn3cUiNgh1vkJZ1WAxfM9cI7gbsrDEI+b4rpG+8pYSt5jj4X487J+SJOWzCek5jbT9IDO99HeGEutWVp14QSu/a74WZfjG4H+r/oE+9Q+w/hkXy/q+HwvvWEc/e/WMnn72Aked3+3ldz+6TH5neFU/zdPj/RzsU/8g619xpawvKoT3NEc/ET2xp5+Intrruwi+m/tzb2tNPt5PE96aBPTH/ymq/m7Urxmu6te4xJzdqF+ji0j7pXjW0yOLBWOJ0iOHATNQ5codruTI4kuEl3vmfFeiZUQOYZ5jA4+trNMGRtbiXZ2WGHFdrNqmPDoZ678Fcij/KlFIX87X5iMtIr0ObQ2K/PPRh1eG9g9smKElRxgvZIpBka+XPrxyv+4qyAPf24Q2QzuAU+CvjOWTPBb19rwngrur8ftzEfz6tMENkZuHNOwdP7RhDOvMkP7LyMUYnzupdeVolNW4cuTzrIGtKwX0rRmAnYC+tTOxLtsllrQk+ha1/OE+scqFsjyR6fdADudDbpeJRP8YX35s9P35sfbx5ZN0kTGpvbVskj4U/0eXTxqQmjFJT8+YFLoGOvzS/FhoFv4/kR9j/IgBudsM+yUJ8r3tKeiIaFcTSf78M0ShG7Jfv39mrG0B9IQl+THK/TqhR9qrwUuX58d2zjViAx7Kj+mP58v5Gm70Mat8kpGUMcnWLZsNuX/Bfpr0eXdulDp5aJjlLx8Q2AWaOO+AoiM+a0peFRyEDHKJRS2qPKOxGnV2gVbmnh2dwHUqGy8KN2PcGeJ3LeyDa9GJP8ZthCaDj2MeGYDTT/B9BnSlg+gndHtSQw73L6biN+TkQf2SScZo0RSdJmLAo+rOtSK4yOWruJvjBQ/vHP7H7LKhvuwilyhy2k8hjGPE7MkTFySKQI2eFqkcQFq4ZBLb4Ldsw/n9Y0fNQvaXNW/Bxk+uFIXdmFsm7ceXRPDBA8pPr4OvPZZrTCw6At1H+ucr5/nM2ydw7m7rHWMhHhOi0DNPvit+TDcmfQSdPFfPrG4+SXjXHzGLQuW0XX7XQj1dg55XbI8TuBXuMr2HV13cEJ5mxNrWGkH632eI9Ool0IdiNUasVij5NOqA0tE61R5EYyFog+9WnCFiGQeU/9WuuzhFxNoB2yEH1N6dXf6Hc0QsBWV8jlrtPD5BxAagrNtR74lzoQOyTcCU8TMrf4S1AP11ZBtd9+cYXcSrHS6xz43fF+AvzHg9oRV4xoqimYfua2XMEPf5OYa2/ZBbaMcu/w+e43UyGz/r9ZzV+JH1TP2UZS38HnqZXQfyvuVdlGVDzyA+xtDHQKyF71wj9gRgmj17/Ebfj4yY/P976rCjqm9JEt4Vn13Y8Dj0uGWd97XmCcZE+So0rf6OQ2z/1vEbNcY+4Znlf4S++t1+xmaqMk/1+I0sj6CsGXWd3+9CmcB76ZOlH/7WuRvzS6PFi9BG2ey5G7cY0eItKMsTroIq/P7xfumPB06UBV1oh/FnHHc64B2aEi8bymfUycdvxjSmWu/t5yTrmXue3Pt045kwCOMbzYJBeIr124LDnk7gFNbiao2+xdqKl2HP2nNu2q9oXHPMrRU621/3qz1Ozrm+Qg/a9Z/er3y6mxNEsNKVXsD1bx4bneDjUVRPesCN94MOK11x9hFzxMwzZGxQxX3gJVE+nysCnAf1kQNHVGwfbZMvuvEuX+kS/PYOvP/Kej/zZLl3U3AbynazjXNUG7IPlLWhTOoVWtI5xYQRdAvqFV+y7smqf+4X/gx1P0ZZuJy20+9ayM9nyXaEn/yCsvHqAaJId9BpsxbnJ9wPa3PQdClomr73D4eJonzHN7VHFW23QdegDpkMnXkr9CDy7N0PQNakpt5Bvj0APH3W0AdWusHXybd3LzZim4Q70nG3EUsEj3c/5ODlcxUvPwV8/Pewx8i3/gDe9tP90haJrQafErOr5gn92uL6P/6xwvfH4B3N99WvEt2zWoVbDAtj/T0OPln1Qe8xMu764Kmi8GK0d+glyh7VZhT8ie12gkcZR2ZMiPvSRzWeTlx456EKwmDzO8/eoS3MW5XXPXOZZ6FvKvvMFa5qUb8oO4z5d+oJjbSdHtrfN7Zf7m8VtJm1LT/Zr2wnPneCvmPfKzlDGeN61yyy+SJtC8qqD79XfI517PKPxonYe9Z3nRZvY/nHSSL2tlV+wFH+wVkittUq3+8oby0Usdes8oOO8g8nitgGlJvgg3z3Onjjk9mKF3Jv+Ab8bj4PNnqW4pfArQKjwyyU9FE/PHDe94o2VnerNfwx4PkI4FMDHag68MDKZuAndT/qS/oG09t0hL70nEbqVmvXm94GPFNno840E3hGnYnPL1o0QLx/+oS3JpAWhFFfcarc60gqYPnJR+I0Rnr4I3hHGsqMNCM2Df9PwfweJn1YPoFTxhixBx3Pp3mM2Hw8F6HeLY7yolFG7EbH89gs8Bo8F6LehY7ywnQjVorngRYO3Pu9iq2SsKkcFDi4T8Hmum4ZV1mQZMl+2gm090zMwWnLfY96Tny4qr/1BT5M7W8dgQ8X9ocnwIcSq/yQo/wj4MOk/vAE+DDeKidOEB+49sQBrv8mlN2Pshuy4/KyudUsXGj5FJZj7rTzNcCHOtfoceAvbhVL+ek+FZtCm13CqDk5cBn62ppiBOU3bqW3vde3nkgJlKHe2oryXvXe2Ee/j/iOdemrZ/2JqDc/g/6IkY0P7lP05EkXTeJUI1ifNnSCbccJ0GBoPnQnrEuuyInMG9i8MmtF3cqsGrFKQLZu2ad8G5Vu0TRxvtn0R/SzEn1Pak8PYP1aKKtvuKd445NyrCMa26TPJFPGBHZC91mzjzSVFfHdDdsRY1kZVbEFtp+kDbpAu+4u4FxeP2JOOAB95a5Li/2w/wt9Fxkbv9nH2IyMyGqT36c15mNe1TGFT28eNkdU5qt9aPKutagbAh55gT+UI5QnlC8fAi+nWXR5iPoreB/53lP0fx1PlwMvbX7BlDJiFnCbesqP0EZlQby/B/YpPWsiyuX6GGmBc1FWbo3vTxgfbWLiOXH+PInX4jtpd4thgTa08TvUr3eLwp5yzzBp19/Pct1RXjlM2vX3cY5CFFXmG5NIKyPRJvsKgXYyne3Xq/p3oL5YZMbb8Q0M0BfyC5QbtWZhpRV/MklftjIB32dzHwT/z8V/VzfjwUt7YrF27OuJISgO5ZQGOX++/w3+X3pY1dVqITf3yb36OXmiviKtuTb7oNw3HNlYw/r4f76Fj6GIuT4KfHhYvlf4UHjY2mPqE9tm6tnvE+4qjkSTZyW478T9Jca2+fYpXxT34Oz1Ofi8CN6zT8WYVA6Ox7vdtU/xpwTMKVckVJ+7/bfZ1Ptn6GJO+HYRu+4fddlhPSnwj33Sx1YUSisLitT04bkeY059Gffx61tC5XIPbl1ly5SYBvmfJ66eVMWUEEtmxnxni/XEhwzGyoQyArehnWZ5Pk+N62oFn30ZzY+t5J7Ka9/RPlndEr4eerqG/vylwfBaxr7CNk0Hb1morRJJH64M4T3t2rZyd0BPUnpj/Qm+lg6/iG1Em/SZiCtEU+WiHwV02Gtr8dtIFFflJok5D/5SeEtrXNMZu8UYp5lX5vlPdG8+z7z577+cIYSkL/OZdb/Mu/NE1Dn5xBm6Vu1xCe8N11ZtzJcy310tPPdnzxDZ1bdCd5p1cZ4/L0kMm+mmLgp9wLMom98wtqMqiWUaymox9oTpjCUL3w17cfa9raHp4J/TjdizmHMINmF9vmiq0cU+7huSr167IHf6AX3UWAOwzbBiCDKNQQHautxHDD0gYsSPD6x9m1/u66N3jHb3nJGLfGedq5Pn/LKqqyBX5XoJ6DaJcp/ljrYVIliWAH2rZvUqQZ+7p74lpmcXFGbNDrSBvhbRF1WT0GAmJja0LROMPxze5oe8egZ/W/FXjTX7xeAAxjDJlwG6ZPtLZ8bCJWI97aRwiYphPnWUkH3nMObfz7GvG15FuLwigm3gUeEVRnCs0Afa9m956qfZHCfHOGvJyJxKkbfKzbNwLTwbCn1MuIFz1I+0qSViQHUZ2jpp3W+yF6xbhTVKrtaOcg/+oYrOZdD50MZdNZ5VhGk2YMn22Q73N2gXc99HdO94CzrNtlwxIvKMW431trlLWjQxyM+4ntWDRZGcV6pYP5ryO1HGYg7nfmxomRYMlScE2ldowUu/U7Q/6IjpvTZRrdEAxxqV8hyjnoI1ypJr1GKt0Q+Np/GwybNz60Zg7KHrEwLh540gx3AIfXIM3FOhzAljHGHgRftp+vzwKi0I+mhpn6zPN0v0+WPQT30G+FZJ+fzmc0Ux+6uW8xuo5peo5lc1Het2Zvn8PN1XUSLErcZE4Q3tlnsnc0KfG0F3Vuk9l58L+IDGwtDnBejs3I57WpvLIVs/WbBxRrkn8vRt+GarEfRcCFqebMTqk0VTGP9pY4Qw9seI+9dFNzQPE01dGPfBBULqMJSnoSnKb7LGNWKbJkb4Q+1GcNJ31rnLK4W30yX8JuRhO9b34ALu8TEeVgT/pYl08hYX4K1gqflT5b5Yqh+wTMrj/tYocYfne9Nbp2sytvswdIAo12Ky2iuk/XQr+so5G3oDZORczPEiPHOvNvwMbQdXQOuue2vTZJ1xwuvSriwP2udtQ+WajIP83Xd97YCsnn3URGutuT/hPFNg71PI/Qk9W8XHlTOuUu0/lDv2Hn5N2E0GD3CLF6oOQifAOE9Amd0W2/ZY8XR92+RejPmIiH1wCDYrdZBMUXT4esztEUVXNYBLsi68I+6FzHGJpuwPllYcuv3xinNF/R0TJtXf0cs/Bftq8ndqf6eZezVoI0sfMbAzYcVA+k0bMHfTlV3d2bIym76jh23eA/7SBr5AGxM8ItYNHUTanm7xfp5wgac2ryS/p3y5He8mfNf7vFLzaCHXrUsfWdDxihG01y9UrNavY5YIxr41V7xSrNZwFHjAKNA/dPuKVpR3zIK9p4ml6aClVamfZS9Ylp2zsOa8VQkW3twgccbtJz8z3IqfcR/4GLpMFfsuB6wWg95Cat+lgrygHTR4EHzg4m8VH7gNfGCFxat1x1xWSz5A3BghcWP7t3E+4ByD6DYL24F7dwEXNWNJSwf3tcfNa3UBfqsLuNbCT7jRBnc3e2K5r3ti1y/VguXLtSDoN3Yn2lvuGuXneVttnPFonk8LMAZi8T15G31H696qRxu/Bu/MtPDatW5JC2VNrcvlv3uKWK77lrQsd+n8PticLtaTJkgPpIXMOC0s7Y8W/vGtI95qj9mLFi6w5ns+dZ+cUsr6fZe/ZnpLIf/aphsv5i00lomkzSshWyNLXjW9PK8dLpd4v+8SPIuhzZ/lS3vdU2B4mldSxkDeriTefEbbErzxqW+AlwtE0PjKLFrJlE3k2+WZgdpvZZxagS8/OiG8A3xpN/DncGkwT+1PS50jb6FY1Xa9ogueo7rkS9ObBboQX5pNbCMHtDEZdBGaIRgjtV34MgPoK5aBeYesNsNok3ve3H/Is/SY8PWMOQF97AbtLjCCYdBX3iT6oLIGZiU+PjBXz6nmmLNaV2VTh/jFLur9WQWV39J/lhC4g3Oaoc7KTPtWngcs8HWbxZ2gA8L8VifMzxFetf+XXcC472IL5gelrzS74GO0tb7LbAqDj5q3Fk2kj7OMdVCmFQL3CkWgxMeze5fcs1qoWB77uR76kq3PlaIdxrkaUbPpLaynSzzUInkxbAonPx4s8XqwxY9dkh+H/h7nx0+A3mk3uYSKX6dux/H06HMvmOsF9zen0/eO/9CpnsNarz4H6wecK4T8kfH/DhjUfmnjndKJ/vKNgsEVjJf9tjdvoR27menL5uUMzz0L/PsL4Fnb/RUa6lVhDtwLeePIsWMcifd3YuydFp0nO9rd/Lot7xWdf2T176HtBRkpUkVRJ2Qi/aDK/zSi4Kpv5BmFFzxvmt4OykyUtbWzbXU2gvUuQJ3mlOjL7eXcw/C1UCegrNz1NeD1urmhb3kI5dSXw5CVWKcNoQ/NJsraeYAt+csAB2/RTuO3A/x9eUvHFCPm7sNf7gZcOl0Z/lAf/tIO/hICfxGnKf5y6BnaZ4pfJFg8JuxK8P/8IrE8ETym05XINoJcR5GjdMc29Fclccfl59kRwt8FO2NRsig8DB10JtaiEzx+ooJbI/iGpIsY5srxtMO2bqOfT2D9XSJm2wvPkYaon7wCux//aR/4Dple2lzNf1Mwl2vxvII5YU+47/5a5jeQMGQs6CPfOPh5ruhZZ9LaT79R9piKJx1R0I1v138BmKNOrcytkBnInV008SaO5fP/jd5s++1GtKWB3vI+M5s+Bh5R5r3ylrm+L17ORdslkqYekj4dvnO/uISxpt/nybV1U/cDfHQ/84oQ1nWQ3fQHh6oBv21GsGOZtG8i9S53YO8pddk3zs6ZTrz4s9CnLnaLq+pAJ7cM4/6nmHNDMuz2oXUr7wfu3N99YSt9rXUTxb4HR8COxdpxzTpgU7TBZtjffXw+kSL5REovPlH5TJxPPIp1V7HEvorHaaMPFN5x3yib2knPm3meZRz44HDGSoulF0Dmt+WkBMJYT8ZWRpUe3gj4gceLGG2d8GJXsBY2XdvAAfOpW4f9LqlH78wZMN/MHTC/4mupQ8R8w6PFzc8Af3IvnO97JnGCz82zWCJ4sEbEuJfW7IrrgMSxMPQkSf9fy3PGUs7fgnkerCGuJUsdXHOB90AHFw1mkxM2rJskYaJBJ0jqBZf6p3rrs5fTz4o+qiw87cvf3gI+CNQbYfHK/3ztkBcdvXnV9V8rXnWC9E9kF0zF8yX83uKPlUnCSx3sEOisA7YhdTJbp37ra7WHR/ypZyyMEME/YGy7gFcsKxUJ2/KMsdvq0O/TycCfU8W+C9DnmKX3r6Qe5QfPSIG8JV7tRXmeZ9vKPOqICxtX5Y15fSXjRfKAazuAm3nAtzF5dSslPi+9sDV8M+O/jdhHLrEtBBwmXhPncsdpc2b6ftxFXEz6D3Ac43ChH9q1wqf2TYjbwEX5jQG7mDhLPxO/uQi4Rr/tvZjbDuId4JSA39/SRw05cTd+f0ofGfVcn/Kpcc10tMd27Dbbl8Xb5LjOwjc2vnCdxB/BiwjfI2pN26Ff2nAmjHmOti+8fod5EFbJgFme558WrBp6wYpwyrPosgR0+TbPT2AcL6M98tARCxOmZ41uXkm9eUTqCP+zWGvyxl5+qK0u6YeSuQ36+KKuBo3ZMdB23DN9U59+pfIWOM9c8ux/61fqvMDqRYzTM2R+qLRP7t5IHbH0e+nTLazHO7HECFamiaJ6wC8N+nwa9HnqpYyD2O8av6pquBH4NXTUMOwi+qHCD0A2SHpxSR06RNsd/V2L8dn2S+XRHW8xnuNUl/DKPk5VOi31e8pe9O216zQMBn4u1eaIRPzHt4wrtt+NBd35zjAe5RwEZN95aKfynsqN2jgxPLxYBCkTBWTqH3XhD0PeTtxaGfP8ozLG89GUaaEHQB+DRGFoMXgEZJ5I0oblidIXxcJ5rU+gTq1Z9xb30CtdrkC6JT9DMo52OH0uQdCVhMvrpFHoRXIuhbDFAEfS966vHLoIzzwudvX4HmZ9ZcX14vsmeQYxU+ZxCFwgltvzuzhBeINo06xJaXBPL5d+hxDaOGm81C+Yn6blz+hr51oRbJ+qze+AnG+/XpufhLbZblUP3zIm1cOeCk0rnd8sRDH7Ygz+r9EX1+YJnolEmyOtcW90jHs1xz2L4x4px/0ba9zMneSx4v36jfXb6urJGWH3dx36W27lXPremjPLvShnW1+zTeYpumFKrF2eBxtRIOV1cybhHfsr+mb+FOonuZCVbbABZSxOCWNS61uyRNa23HJjX9ay2pU5+M25/MY5F+Bbu57T2Aa5E97KOWUXBCLQAaAnCJflJ6HegHd56VdPmvCVPBO4/rDVB/GH/S6G/RgF/txBPRYyzkOZDX3JN1r4RXOl9LvRzpD7oz7fSuLazZzvFJ4BBp4L1zb6+RnTzHe1ozW/B999b58jc4s5gx6BDb81SdK7fW6Re+eke9KxTeP1oPFQRO2TEJah50WwLgW6d6bwngtYXtQ6JdYMXkf/7eb7Z8Zox1GPa9O1IOTunC1LZkr+vOUh/H8e/x/H/1X4/wT+f466SVdPOpBYl922SgO/vnrSVt9MnmMOuoZePUkARrADgu3A/bZ/QCeFfZj8svC2PY95w0YMJ8p98KkC9uQMvHvbrXnLUA75OZU2ZjgiYtz3CNeJWLjOiOVb3/C9Z2H9KtqljNEK4T334jr2mSton2pGfYuRavhd7vqWUU9XP0oZ/ATWPAz5Vqe7Ik+MXrSyRKi91PuzjXvqyUPBk+lLoF07iragPqqxPx8P++mOKH82cZJt1CSCJ0GPyZexSmkF9rn2Tvwmv90F/CjHN+GtiQGuZzNjWr9kjosZDe2xP7XMuvXV77WLl7SsvbP1+zBs9MVZHd8Pgc6/C3giustbXxdD/B23Q24u3LrqDeggOx/A7+4LWg2hrQq9JGJ10I+GnrWkpVkM9YceEbTXY8Pu4LOKLx/+K/4e7g9NBRylHi5ixmL6LAwZ5y+MskngekXUqdun06bxFIiFudND4BeMxXFnGfcwf0MI418kzxpCTjSPCHBe72IehzDOA3iXhjV7jLob2onnb8kqOAtzN+zcNND7+L53jpesglMikm+8vDriyPGyNrFXjhfDyvESBq+PRrTgwW+14IfovwN0Ue/YWxlDmgWeX2zxgqdcOduidxux3dAfdkGnE9OMRzXxmxb6aZpThX9AIvenLwa9zQ7smJc/7xRxaiwRf6ENhtRVPJHohtDtRmwAeHzoeiu+vXIw/Y1J1wGOPb6Vw4DrQJ69sPz/kT7+Rq6/5WOJfKn4JPGMe+3jI8pPaOckcfJNxS+TJK/cBZ7IfcFBjNd7APoavtU67mkVPl9LiRi6b6SA/eYBT4GedQBr2SwG+aOPGLHBlUtaDk8TsTLg+eG5IvY5bP3QBhFLIc4CRklyv9TXkoq/kdCNeHbEnAG+Bv3bjIjgrpoh3GOIddekN3C/EaBtMP8hYp3LtCAsnqDRqnRmnrmgPGlOozzh/oI7EnqgLlsTKSnhNA32SsqtYdCKL1sEZuo8VzLQTz5TfaS0Na+7tLVaq11ZpdOfmyp9Mw+hvC2tNCjwru1zLfiQ5ltZqomKnrZX1GUnC63g7SGQ0wu4r57TeBgw2q8nNR6ainnJ8xxJ/g7g6pfUF1eIWOQVEdtbpwW/2oH5RSDbp6n9rJCMOSztOlhcl70mnXG36HemKGwrIU1ojeEHpB6yjbJ89SzR1D6DfFyPNPxY85K30M+V/xi+82P8IYwH34Xnsk1tG+nuIODI2EvQlfQDhzAe0iFj36jj5MHWo+0QnkW+d8EkTdOKiG+Msz0EmRQFraTfMDiwHzhDeN8IeHdjvgK6o/RH/kXFKcocOUFR1Cz1hFGRNcS9myF/dLGNcuft1cLL7w+jnQNo1+1bBBiN9EfRTzdokrGylo8z2EE/PuiF83OBZnSMzweaIS93gWbyxNIK0g19aLXzRs8LP0P/8amxMOa5QNLVqeC5OZGtLeD7D1zSQJholn+5BPYBYRWeQbiKCuhugTBwLgxbtkiIAp5hythvFnXIvfGcxsgrRmwPxvfVDgNjH9H4Jb6lvy28TMF+b8T0HpxGGyezcTf674ZOdxjwP4D12oV5dK8FfiwrDf5YE+llzP2nMXcPdP7c3vln6kXzZ/RhUpcUC/U08asTpld6mlf+WXh+N0No1RrkuV0nDNxsm6v4NH0r0J/81DlcwBOu61z6XzDGcqwt5WD7MkPuJdE3mQvcSbpQeNO4r0NcmabmQZiAR1eETmHcr1bQBrwpy9AKWR46gXkdS4NGtiiycSgkcS8t8uAiIX0Du6cxLjZtG/TXWH052l6Ftb9ArKfeEbL6uGQ4dSPqMxmNmiECe8BzTZSD93rN1tLzWX44UbuiROw4bw9w/2RDvG8+MvmXRxKzfn70es/gnfpNf9qUu2nwq/j9n1fOHhzCM8/NNuP/E3gmPMqJawegg6OMz8zbk/w34Z0pBOxLEWB/LvD0XC0xsmWQ8ArNmBS+W+3Phnx4HiACuSIx0gbZow0wJrXjHeit2lOLd8n8Hu3xXXL8XT2/G6S+yx+Id4Mc3/HdMPWuDHJIG+Z4txjvMtS7mbB5tYz4O98DeDdSvVsEu1obGX8n/oV3J6h3ayCXtBMcbX6Gd3nq3Rbo6lpe/F2I706y5jcA705ytNmOd2PVOxffjXW8S9K84nRrfm68O90xzkS8O9uaH893nu34ju+KrPkxZ1WRY5zJeDfJmh9pYpIDnuzvfGt+9HudH3/X/DVwiLFP4Gek9/0zshu4T3iAegt43n7g2iHgfKZHBMhvnPaG7wytqMaVHrnlffAmtDfTlb6NZx7m74WetErqxzIGuPko+OxclUc1DD1zitC3UV8jTu8WmX6Oa/Fkzct4ngO6q/EjeVZ0RKS2m755V6NNn6TJQ9MNSZcHnuFYr2vIsmwUSUOgFaMaOj5olb9JI2MzwNctmmmrVnMi76fPbWYDbNMMrRdN9dDtijjdLuoUkm6bu80ipzygrDoEuB0if5qW3XAA/Owg+NNUwIg8imcS6QOO3i1idh+C+yg+6Lu7IbcA9+nkNVPIe3YktTF2YYcWTGbM0x65hyhzu9afGn35sr0On/s/FO+/Wa5Fot+NtYAtJXOC0N6i38TNePVVVzSQf5L3duMd+Sp1S/LVKHhx6BnyYNRnLP3o6xpk7AT4kuLF4K0zlCylTrkT8r+5LDrhDQEeBjjmJUFvrhvSIJJg44CH7llBeSim7pysBUdCh+T4brX9jBhf5VFRtH+FEdvkckceBH4euJs+X2j+IiPiwvMalxu446YuWcDzw3swfzfwBfrVesKHNtlby4BngBls+ZgbcPRd+dOuG3S3v3GpkLLbk4ZxwLZI0sRU2gK5qeKFpHvVWJKK6lZG0U7yHUq/yYIe2NopmjxJb63kGbdE6Fb7gV8d0KvMBSK2Z/HQhhD0zNgq+roS/Ywl4XoTh7g/GYIe5V0oVhHPlqdsXskYly1LhJexnMsz61bGFjDeD7KesfNY/yjhDzzh2pJWGPv9PObYPEA00f+QIfOepUfeTlQ8PU9Pp+4UWfOAWuubJCwTFN09ZRa59Ixtm1xZkbXgvcSjNdSP3xso8zX+GDjFMxTUX/++x2Eb30DbOBN4MgpwzpF48s/dyjZWejz0k/emNtQDLhzjQWlHi8Z5MmddRuMh2D2L0J6vy5T7B5qesw0y3s9+nnT0U1rDfjJ69bPO6qfyPtHEcxxsk+1zzkt4JpzxvHMpc3O2HeR+UrGCH3V+gzQCfWpZu2iirkU9i7pVaR30U6zRAOiH1JOpQ3HPKobvCTPu80ZvlvvK/kOPkF9Iv+WkyiohdTJxg4qr8UA/3Aw9K3S3pMO3dIwtX2Rto15owLYvRVu673fSr1+2mLnRdX8J8PFB2pzQx4ibyT8V3v0zSFcjGw/I/TPwEehcOvStk1E/ZD7S0l6jzgt1AIcqH/WtdBnDzqlK1fxl54nhAn81oI0s6TNYlJ0v9bLZgcp5J88jvhu0ZXjmh/9JDyIrokOGEifDJepML/dHZT5DyCWpoy4Wsengj9Mv6K2bLHJpXqfeUf8jrAl9InWlwVBE8VHyUMk/I7zORdvGPNfrmYN7ldJNml8xmxjjVg/cZa4dqZO+a3qpZ5M+yO9Jq2Xg9e2zVDzCaPymvvTgO6Z3J3g6y8mbKmnTKd64bbNwb2O/PpQlnvXblZvIh8QFXW9tNL0f/tNcT1mwivvPu0GLWPMoYC3SjC7y6z3nCO/GIVpTsytL0esO6Fgt8kxsYydw6cC06xqIW4fA9zjX8KwrGqjDSl6H9tYMRzvgcxIu4IO+jaKIZ1Js3ewtntunbLF01fI2y05gHA7GxfhmwoYwXH5EySUZF5Km4Po7xjQTztXKd9T+BP1ujH2x5AN9LHOVjWHWiFg+5Bzr76EvXH0zZ6bL6Co/DzzBQQd5/1D4fCLoYD++ywBehyT/Ac8BDXZjzjxDTpuFdBG17KtDgMmdkq+kK//hsPgZKcZtVkI/9Zm0P7J67A9h2R/JgxRfYv6y/bTHYXtQvx8OO+Sw7G84eBD7zpB7RuSbpAHaIqSBKtAGaWAG4Eo6sGlgKOhltBjqr02ljhGnAx/sEtoixGtJC9MVLdAumXUW1mGT0i/aNmG9nsJ48Dv0FH6vKmUOiyLfoftaGXttxzGEV5QGV/tEEfl2aPSilSF+B5sxBDuYNj79Owt2gWdhXejfIe3Qx0P/juviJbId+nh26jMa2rT67zug52tzYIPRhli4dRVj8Gbx6qTuC1ofE3rBn4VrVeglmWNE4jfH6Frq7dILFA0PvlLt3acJwGlrqYoHk+dNvF1JAepKmAdjRTFu7hmIN1BGPw9te6y5ibnufEnE9s/NaljLfRSsDc8bcn9rmLQNXf5S4owYJm3CSuYBgP1LGTKLdvLRHUtCWH/oBPG+h/64azb0b1+qryIL/JttOvEl9I1Z2FdfODhFSH3R1htI39QdqHtQ76AtRxtu1+hpDdSRfK+ZxaGpykcTLld0sfdV0MUjMt8XnrMiM1+1zs/o2jbam3lLF8l4lDWvmN5JgOciIZa2g+/Sn0X/Fn1b+/Gfvq0O8IE/8Hxw3cCGne0iOBxrmg79JCT9W8yBltY4f5fKXbycvq2XhZf5ep3v5+xSuYsju47v17JzF2tNkH30wUW04KFvteCJ+GYnc32DjqhvUb603UxbkjLG1SNjTmGePF3x9UWwt+RZI13hStLS2pU7XEmRLftNr65lbrN8eEttH94hPO9pFbHPd/adW2ZjmWNuzdAtPuo1t8zGc625Nf0Pc9s8ID63xbS5Mb9dO5XvrlaX+Yoirm8gyw8r36QYx3sxlB/tiV2OnClfmZYfTcWMjNyl/GhVzEHKnKa3G7Esey8GeNmsicK8cYwhErFCq70lu/rzy6n2Buyy43CyGi9Fm3tajdhsHXipJzVeTn/i84aMc9r7hJBxTsofzWvXfC3SZ01fdUTE6B+putT0XtdljmBblCMhyAzKEsoQyhPpB6CseYVrW9oaekXp0M3Xw2aAHPX5lD0iZemnimZtP9Piyyw5Db5MGcH4ASl/LVtHxghA/ph+5gSF3JiuaP0GxsLb31HOopwyowy0wPc/5XtLljvl1dZnlc2V6xH7kq8Q0i4aw/gL+j484n3KYylzILc70CdzYNlym3Z//uuQ22h3+FHIsX5sKvLSt38EfvEY4zC0xoP0y1m20tmH43baVfi+DLDNq6Hel9Qo+6dtKGHg2sa5rzms6oTvM73Mg8HfVah/0Podxu/v5Z5cnAfeeFju88bCLuhecwB/4FGOA49CzLPqwE3bx3tw5/F9vHfstGJKIdtutsYdXmh6mT9b2oRbzSLGuPkG077WIrMfAW7/o5SxO3PCryj76a3fY56fSx65z9hiNl3OZ8jMyjeBG5asacNa7ujguYEZDTshb26ErNEhZ/4MedMO+fIbyBolW95YRZniEfqqcI2Cffhztb4zN4FPAi95DorjrJ1nehs4Tkv/qDWVXNAhD5QsGOlnbArnXs/cUGeJphrXqEj5KCUPmk/sKw+u7VqSoeTB8p1KHtwo5YHyXVZeZxaS39MPTX6/3/LdRS3fndQHwPt3P6N8eDd2M+dnWiP1/INzmV8zq/Fg69QG6vzU/229n3nKx9ab0i6ifCDOi7Ou7lpcZ3r3A7cPyzMqsKksOVKfK5qoI1NHfwvyS9rd3TuWiOS+8/F2LXGp+VRa83HGhob+BPn2PGNglU7fMZf2IOD0oFm8B7bsrrppDTsnlwavBF7QT3tIxRnIfm85oni4x+LhA8DD61wDImu6Te9akX4MD6e82ok+bu04Vj693xHn4b7MY+XT2x2Kh5fv/O88vDb9WB5+V4fi4ZtdKiaMMnbLod583KaVAgetrD5o9qKVpzoUrTxFnLPWgjQ40qZBax24px4DbqzkHScWXx9vtT/c0T5jbpztP2K1z2/9HC9tthXHl6nndKn1oP985pdqPXzWeiRiPXL1xMiavaa3HbZe3/U4jOfdkKkJ6DOrZz2ypD17m7UeWVhn3q+yQLfXQ72/0VoP0vN/lanJx67HMGs9SJOE36jjyMLJFsze6OiPf+VImJVZMON+A7/3hc1CrnMJ9O78cO81zrHae8HRnhYye7V3htVeF+MraVMB/w6CRrk3TRlJ2q0DniYNE17SdFq35JMxn0s0Nt8AuvSr98vzfSs3HFZ4snO6zHHMHLqNKhZK5adle2yfbdKvQd8AfQQx9L27lXuC9KskNn6BZ6ftnd9NeS2k/+M+51y0Y/0Sv2tX57eaGUcIO3v50abf3aWn+7knx33eWymHyDNhlzj3F7TLjEcps+gLKJ1XNS9vovGoyqeWpeL76NNjHVEKPntqwJhXGaU9fiXam8UcLNa+RVuur6Vev+lPcp/C2o+w9ytU3PXNf3ott2ZwjdCqGV/Cuj37FXZ9yoUxvfctWmJxGnRVLmmZSf0fcKgdouSirV8ZoMfQj0RRFDT1NcZm7ydxDykqbcSMxl+xrbnUDcS2Hr2jWtmrlLvUTUpYB7QV3gCeh7b/HMWa1BjSPjwk7U3ufSl78F6e0wXfJn485JTZ+cfKbMrdynFmv3I7seP4cvv+9rjcnh6z7O46uQ8a+90RJS9oH5h7zBXcoz8H4z1IOTlX6VxS/8KYfFeib0t2158L/K1R/l/3W0aX2mvUtjVPUzQi5Tjh2PbDcrxtirXX9AOyfPTlptQNpe43Pe4TIOw7MFb2PR5yztavevw5ttzE2nTyrCPGTVuKMRa0pxKShP/NaE1rrq5FHjwFOChtqoRI2SkyN1CkoRA0gvFxHzdB17ftwFg2k1fi/5bxjFNT/q5LfoE5T4n7A7ZUE+eBC1MUz9Kc+HVr7/WzbYIV7Y71u6W3TZBurd/FmEMb6FK7X8mlWy5SOjP7zJ9teoWlJ2rnmN5fHlF+EvpqZp/Sx1dzL76zfDS2js11lv6aEqVjn0I8+dzS3WBne5JK75Ex3Su0IHVP6rflv1D7c2HYEAJwDFULOZZLqlUMH/0H8hyWZcMbsN8bZgOmpBfYGRdC9rdBZ6gC3dZg3FjzqcwbFI6gPZ7J8NWt5P7Kap7JXLhmVZ5b5vnbl4e+xNDFch2YX2h0UvNKypzmG6PFmyDvZgrxXf3SxSspuyhzbBuY+hNlmxc4mdEjxzKk3vBKm5Jj68GPPbOceoV6/1KbkmOnt/93OZZXdawcm9Gm5JjUmU8yvQlYH7mPQ/uJOK2PaOQ+DvkV93K4DuRta6OWfYBvYpQfO0qDAryhXZ65V7aXLWtog3Fdh1i4TjzXmBMReF4GmPHM1d6Rwltl+Q7WjFR4nnyy8BLHZ+qjtvH8SamF42UnKRyXZ6ySTG8l8Jsx22X4LfOo9pHHvsT+eVOozRH3m9Bbj/lZm8Lt0zFP4jV1do4teaTCbY7jbTfsm07go+WzbfPinWXTzbXgo51gel8AfATmy3GSh7atKg0uShNFbVuN2EyXK9IGnuEpxrf/ULpPHcpm8y69pA9WMk6KsnjmbaBd+pUglyrxezHz9QOHZwE+Ppcu9yHa0T/P6DGWaEyWcU8z6P2AhWfEL+IfcW/nUyIWDKs4KeIz8S+MMbTRz1mjzieegPnXA+/o+8xjDB3q1IO38H3bLHXmKkReh7osG8b6R82X/W3Hx0Nh4WHV2cfi4WsYD+8YfHOQWC8O3Ne6/ejxcWUJ+MbMDPrDc+RaZ/wP9uONbceXQ21hWw5lNH7cpezVHvv/HfP/O/sfeMFYu9Lhpvfs7rh955Rd/OYb1OuP705yjLe0uTfffdkaL/WBveCHW1IVzM5z2JH0a7AfI8Nsopwnv1zkMroWXR/HI8/1lr4NXJL4UwS4YF2qrjOLiTfkeXNMhx+jxJJ1lv/bjrcZizlwLLdizTRPaXD1zqOFPB+gXZnnb6dOuJx3JeiRJYC763HolqCjvV8e9fLuIcKYcR4etLGf+4bWPqs875AnvM7nvDThfRz0U6OPkjG5154iihbBLpT6zeeJAY8m1mUZgwL0l4gry+XZHG0g8HO/OgfcEdHnhw5rQdJCx2F9vmnq83PD6ozi5UOO3cNrZkzyqisauB9Lv6C9B0vfPG3ow1b8y37GKk4R8f1b4MAKwJx6zb95VgBrQ16VfLHpvUvyqozImimm9yrC9hml/20sEEW1mFttcW/9ykf+hXdsy54r7yLcCz5zyBoHY3UYs8NYHcbs7MXaMGYnrVP5PzrIw619eXtP3jMQ/WCsj9Efb+Gy7dsZ12nxruhR7yJLdtfid40tx2NHvQuVr6jF1tfuOQi5MSuuA1ySJbzc++Hv8onKL9BGPoM+OQd7H58xSIxJYhzSfw5ZcujQUe8NVl9VnUe9VfhNu5560wOwLxhbyBjDPeiT8OfzTvw+hDn8ijD9tnw++GlxyCyf7xNiAnFI5qLqrkuiDzDcKvU4fxgwFFngo59rwR6/YIlaT5fI3NYNOLiAz65ss/AQ+nFdme9vp56zXMWjEZ+1x/k7M9LmMS18dkl83mrpfwd1t/Sd2bD98JDiLzLmVIyUOmA47ZKGPXVTG3a2G0Hm8hsaJT0p38XzmJctF7d8bUq5eMknZr9ycdHHppSLN1rxmE5Y/d9BVXY/yh7A8x8PKplEeUNeJ7rrf8d4YZVn4gN55lRIH77iweQP5VjTByeZ3jbAsHawCLTvUHRdBp2G49gy+vj7HTcfUjyolvn6RWnX3glxPrT6bTP+neOb6/DNzqeM2AewIRticVtW2rFzRY9+8XPqnxb9a6D/0Rb98zwT8+DkJcV5QLuDB7RbPODEkOIBz32BcQBnKr9I7IUzO3i+rETFY5C+SW8/FPf2OPCGftVPDip+WOoxC21eyHNRxBPC05drem3eOBs408G4mcf57JZn+9uAO+dwzwE8oD5BFNHG8WRGN9C+4b3Btj3ztx3mip2fy7MIFaHEGQ1//ths4n5YHuwX7oe5rZjnDivmOW/h1lV5sGmE272qQ569cgO/BkTaPmS8HfDhyoD0r+WJ+u8lXoHv2HtmtIXKfL7sJ+lftvpfueOHY6yd38pYauDG+4zDv9vePxoVyY/19nNkWXLw7pDDNxC15aA6u3Fgh5KDf1P7BcH6MWbxaOjuvIdgK+2MPnyUPLT+YG9dcJTVz89C/ekHo2Q/n+2I26mzMO/2DYznNmS+zkHLeB/5IP/16IexVHlP1n6W64ZM+8D3WRXKKB+pO9EG6UsTa4AfKo4yR+JTB/CD+ET8kvhEmbJW4RfxytWpeEf34qQGOzbooIWLHaANfhty4CL3VPjdgUNxeUE5wXv/KCfYD2VGAdaQMuOBg0rWM2acNNe2gXYqxo/2hmCeeWKIfzLmJO1V8ownfZ+RH3k+qP3MQLm5ScRWgneFMden7ZxEsLUei6r1MUaYxY9jrWw5lmbpeDKHhmX72npeiciJzIKMn+lWug3zUq1pVro+fYWXNCtdfxRjdaiDbVA6Kfk423ShPZ6nqLTGnyrHn9ozfo4d+lnE+GDRZ5WMN++Hb5mvqHUyd4hY8UElz522BXFKvBrHJ6lPj5PyPFgKfGJbnOunR+I8fE1M8fCGI/3z8LZuxcN5lunQdGWH0QZb5NJlPB3lNOV3OcaTNVDh7l93OGgEvDS8Nk4jCyzcLXPQK/cxnvsP9fS4/0Oz/B9h2//xTG//R6VFt6+BDxP3iFc2rhKHOywcps7ZF3e9wL8w7EPtBbNQ7htEVOyGc4+O+ax64mtPMXtiX04mTnKPTovH1dp7WbaOztg0A+/tbw4ejO9j7XL8Pvew4st3H7DO9wztm19qYM85nwPWmT6e87HP8/Gcz3maWOpLgL7xH3XWx+c4DxH6jzrv7BvsyD/1CMazQMQ+/Y+KFfQNj7/7AGX0N9o5fn4L/bP+vrxVjFl+D7h8aJgRaKudGQv9ZmZss4tnhZIbpN/jTC3Is0DhB2fGwtBNww/j/zL8/yP+b8D//8P/rSK2OeXqSeHxWnBzAv4/gv/D8X8r/mfif7FG2bvvlrXQ0xgr3d85oSdF73NCn1vnhPzow/8D54Tw/lvgwWcdx54TEk9XPyrjO4Dv9HlRz3B5Fq1se0D6aPZ9a50Vau45K+SSZ4VkPhTU4dmA/s4Lsb/vCM8alRemsk7I3P3N8h5ed0P0NC24/x9a8Nt/o84ppbH+ZBXxnfKKY0gxlrQwRxblVtto1Nd4FvuC1nbwiI7AzFjH86B50IS5zHd+aBt4hTn8OdNMw1/6c+bzvvNhg8cGnsXzKgP9zEfH80HhqeBDv2JZqp/nwHg+iDLEB95RuvC+ZeSbPCtUy7NCD6mcWqdOE96OqeQDE9VZod0iWGedFTK41/8I4xSTaNtvl/sioREBwuIAynhGaBPmy/NCncwlAFqNnVYaVGeBRhaM+U/8vFCzS3j5rvd5oZEFOf9R54Ue+4/zTuj+zwvxvH4MutVBUwu+/W/lV/oWvIv5rszJgBFo9tub8b9dBAGrhujn6Q0m+WzNiAbTr6FsZIP5sYjdb51xqQVcfNY5F08l+MMMI7aCdOFyBz5wQU93uQIzj+54y2OdW83o3vEWfSezmK/pGupDhozHY96aEOp9s1jtazxZUPq3XaCfHZqY8zDvuqcPcGhp184Rddm8U4wxVEnidy3fArZJhfXfnyaS/EkDDN7jN9xl5YZMxZyS8Uc8aV+M+WiiGrq0txZjlzl8MJ4xGI/9fIpwB3ZjHA+LxKkm9Lt85lW7pXJinkjx14lB1c+Ch23Skqv15sXZDZsfzM7DtzyfHwYubNJSq58DbL/SBxWAXwTt/Q3ubZRhbJhHdSrkxo2pomjXj0WRuBfrniBeIJ9hXmyedaKcID6RrkrUt8OqjhJeWqQMumel/C0iow+Y3qSlS1oOupL8zN9K3vivInUWVr7HHJdR1gG/eI4dOvfSGydAh1soGtxXWmdj8e7Ps2/aaJ+N3am7gu0D3fM7BuJ/jnt+GXDD54iNlmdqPsL6DrlgvljHc7EZ8gzlOvTLO+v36IMbv8FaJIuHWuw1GMT8yYS/lQNhINYhGWvV7oAP4eLpsyYnO9ZkDNbkfqzJP4R76g6sydtYAxO48LD8n1KdJwb6uR5fNv9OrsfX+oAC4HiTKVKrb5PrkSjXg7Ask3fgJFVXYR3evRQ252IjKO9YvVvezxwEr5PnLTz7TflMHNfIU+9W/D8b9E8ZMGJo3iriN3HbOovccg/gMAlwpvzwlA+StBeGzpHutuT/v48fZ3Pav5X859l84oQXOJGA9V0+3JcdciX4D93OmJsRjSt4TlGeUVO59XrOh/OcLXA1VHDs2fBm6z3PMvB3jS7muHSj63BxXXaJSK++NLPPWXHU3QJe0cn9JuhRPWUnqLhc9wugecCFc84TaTI3xwjM3Qk/4VLr6XpR5U9R9Vz+QajXfjdp/iHZhkvmMfC1VLldq/SXqPvpfjfq6Gcajy7CXGf5tMBF4Bvhe2ZtPGWcGB5K0oaJs+a1cn8uG3PMYv6nkaLo0sPGozO0rMjTsG19znjOZaLo4GTm4EpoPABeEwMu7If9TryeI/F6mOJbfxdFtZgny12+38lYP5UPKSPSlsa4XczLANxcwOOli7K5hszBwVyKwKuroA9VX8x7YV1iKvOqitR7W43ZlVHaj4u4Ltdb8RQu0RQC3xpauaRlBM+nTmccv4g8/XMrbvB60JeVwy6sX9IgwO/2eFVcRQpwhAcNV7ugV001XmTbF2OddqK9+iuMR3dDDgwWv4HMHezfZT4yfE2q8IfHzWstFxeD/8wOlOqa/y/zxsyrh+6eN9QIzBOnxnSxpEUfU/+9Drhfi2cZ5zhOzT1vOX0h6yr2Qw7sAa1XiaHBIRj3rnbmExwa5NgPQl6sh70xYIAI7MTvA5ChH6SK4W8Cl3bhu1zYq/r1wrt88L2tzBs6YHZhtB7z9PzLLGxLvLRB2ZXQt99l/JImZay0WegTnl0lz9eHvnD4/99h3o+kuP//C0U3P6PeXKzyyT1UaOUEAM7qZULWP2l6eTAE/ke+Rx5o8zwx+56NIfA98kLyvp0W79O/UHl5esXkGIr3yZwAxTIv3vA5hSonQC5tW7RP31YG2uS4X/yiD723k94z5LhrrHHzrDDP8Yf2+4KMtw+BfrqqZbx58Ev6JP8L3vHOX/07s1+8m/WV6Z0fzxvwaAXGSlsOdH5VFnjZ1TxjCZrKJ02hzULgShZ4W5Mr3V8KGlvv0vzLhxvyTordC0Swq1zIexlsubQBML7myugGDTyLNF8K+bTy0dLgiUsVf/gD1pLrMb1m4ypF/yf6T8IYsP5v1f8puoEwpw948wSVnyEX63I34O3BWuVde8/GsK7y2XRgXUID1Rp1YG2e+FzJJeZclPfY/kmtS6UmitnvcHmvF/Ndss/h/iT0ybF2XhrdwHlu53286DPzWrVOFzvWibk41TplynXKsNbpS1Pth1Jn88yu3HhB2FxB/XPxERUbQJ7aVgecyBKB9pvJe1z+MtiNg0AvtB/vYW7OoYtWMh6yTDdkzlie8z2k9qr9nXpOAevRLv5Kz5J7/DE9u3GPki0rB1I3q4Y9tlbEojzvdGZpsPlCUXhg2qUNO2HTRZlXUE9pPIyxHNovYgev5xnR1MYu0OqXwMldkB+7Yc9FXtGCeyIi1vm5Fux8Xp7zkDbaNSNFUxv0/NQ5au1sv+JOmack1b91vFjO+1F3op89I4R3F+RCdDLbZExXZmPkldJgV7vMq4NxD8A4hLQpn/mdKHLy49KvRFEm+OsI4DPHngk+S/0X437RHmMUumYU447Bno+hv2z64iw6EEtXSBoQnscsvptVvfd14c2TdntOZK87zmt9btFUoqdHnr4Ldqe5Y0n9Hcfy1iXVire+ZOHU7LnqfLTcV0gWRVWWTOA9MCViZGTrYdP7Q2PZw/uS9X5oEd/txVw6zEcqyK89lxuPRl9SdndshxFbC15NWObpWVMJ2zbQYolwVyeCnydB98pben/2DeDjs8DHt5A3G8POWT3vVMnLS2WusSUtj5N/g5e75R04Vwbm45l8vK3aCI4GfyY/rwXfLhPaOTb/bscaMsdUEei5EHybZ0rKPwBMwK9plx2kDYD1GD3bEyUMK+8TRdyvz/upaCJcdHlnoIx7lHv3s8Hro597G77FHKMjohOIp+HxPL+nFTRr0HkfXdIS1oTfI9Rde7s0jA9w2WL5e6SN6/D5MP6FeUakfYDf9PU2z1S5BqSsmML26r8PQ3ZIuZEUlxsVn/fNbxqXG+99Zt1zwBgU2KojUJd5BcRxcrSY+kCVm4W+nkfUXNt+LLw7S5TMCQFOTjzX/i2KRgDPDwG+I4DjPB+yE/xzlAOXj69LZFePfV7Fk9hyPhk2JGPYmoHTO3hW7QbY3VgPMTOO09LnMvT6rqdvUjh99DOF09USpwcqnP6zE6dH+HkmYLEDp39oTMRtox/cLsf3O8ut+CSsVRg4Dns3tkZkTuX5cOaXKF1am11j5EeaN4B33Myzezw7nyzxeAtwf/O80fMuAH7Tx0hdpR008Afgbx7o4EJ5/6bmd7krAtRbysTQQDv0OeLz5nn5G+lv2kT/9xrhZeyicP84IFAH+BDkGbDSeZ6NdYTZy9JXMSxEPop1JF4zVoRx/Mwxxzj1kGxLRFyfmt6Nlk5h68GUKXedI5afB55PHOcz3xPXvwWP/SXefYvv5+0xi8mD5PmTacpX9jZzaF5jnc2YbOVG2K18iHZcgpC+xbTILbtM6S9IE2nbOhgnr/wG65x+g5c+pQ8rKRBF/4xxXcFcgqeVWnGsGdInkPmZ8hsw1rV+g/IbrJd+g3idQYoOXn7gs//uN6hdr/wGnaYWfOVT5Tdgrlbqr8nPQG5Ok/qtjAlNwFwoF3NFQiS/Uc3ndcyV8+B8OA/OZxfow4e2RmAOxJ39WJv9pFM5lxEydqbjUxVbwzuzPY9YsTWO9198qmJrfvyZvK+g1xxgNwbrrNiaOsbWPCy87fi2/bAV04C5LLHmUutS5+Coj7atPVYfzbT4ynmfOeJ219j6qNIXgp8qvjKEeoElh8i7nLEPjNk9CL7vlveK9N/H6M/65JRy9FFv9cE2mJvQ7me1C/LjJFHo5Jfsk/p25WJRZOvgGnRwmYcY35+AMdTA/q1fgDWCzlnC9papMx1jf3ycMx30K36uznSIn5ve3V3mCOb9iXYZj3aBD+xeYASf6LbiBFHXRN2D1tnyBsaXPiJzIjdStpM/duZowQ7oKp3XX9pwGDL/wO2XNOxu14K7X+KeS1JjpFUL7vpWxL7sFDJW7CZXYuRNTx3znkgZlDSnR2ZLvvxgjoo72oHfby71rWTeGvze92Z63cr6k8X6r9BvHWxF5nxwlYtAneaKlO9inocLzg+DrzDPgzM+dYbYcd5e3dV4aZ+cD5H/IefDaJ7BekDInA+azPmgRcbWCi/42bYyQ/XNnA8lWqrM+eDRjEltxaXSp2g8iecBrIM2UoU3nzkf8G4G8yWA13mS1TvmfMhPjr+rfw7vBql3Ywfi3aD4u0rywGHq3SUpeDcs/k6Avj0Z6t0tyXiX4WjzJbwbqd49mIR3I+PvjBfx7gT1riER705wfNeMd3nq3dsJeJfn+G4T3p1kzQ/yLf8kx/xew7ux1vz4bmz8ne9VvDvdmh/0vfzT4+88r+Dd2db8YI/nnx1/1xzEuyJrfrDJ84sccNmId5Os+Wl4N8nx3Vt4d741P8jA/PMd44SudPjzxAbGDxyGLtEJHbZzMvdKUhr2A5d4Zj1WndywG7adr88ZD3GvKGpzZW3L1UdE8ufzPH5pkDk+uz+B3L5XNDH+97c8E+yW+9DyDpu2xLpsg7HXu6ln5Gx7/bt7W+kzuV9kbOPeGn0xxLG1X0APA/0dwBh45mN0N/RP8P1d3H/8fEpDJ+guVn1JQwfkAPVw7kl3QsbtvlvGlcXE7WI9daMMXWzbDTnNM7315Lugz90TxPpwpxV31W56d31rQE9XemwUcDhwe3LDoWtELNJaGuwkj2KeBMja3e2lwe5uay/xmmP3EinD9ybyrnlrD+4sFV94C8qYh4v20Rqh946lSFC0Tp5H2t/zk7ivgWWS110fl7t9+WLzxzx32b/fYcsnjjwRH/X2O5R8onjwX4+quEPGAC+eYnoZh7LoF2YhY1B64tuXW++tOBT+HnuRikNhHCzjUK45bI7IH6ty6jnHuBpjDP8pzrvtOS1Fv/TX53YpPtvsjp8dfzBiettq1Nnx8G6uoWvbatjy+fI8uCvy4Jd4P1neR7GNe7GlzAPIeM2PTW+qLvxBtP1nK+5ZxpK1CqkTyTO90HMvgsyonKBi72xY3e2AVek024a28qdbsLoTY620z/QsV/qCfabHqS8sWhbXF9S9y1L/WUqdgXdV3vkx2qMc4no8kNggdYEHpjR8hnIfYyFLrFhI6GTNJwp1dojzgf5t130PdZuPmi9f8sn/sF8y6lidYQG+b4NMq5LnP9IjZQ/31heY/0LuMQM+vIeHMDrjk+PbI898bJ0twdiv6e6tO9hnfqT9Bd3hAGTnZd3H6g7p1lqkf9Kf7qD8zAGrH7Yxudsef2ak7f+O1Xfs9oSzvSd6t3ev1R5zzMozNrPi5yGkfeIShcdr98uP+4OHavdmq13m+XqzW+ENz4OU/VHhjXDgTY0OnHncxpmcbTa+2PryYe6BAG92fWSdB+vRk3MaL//YcV450Tp/5Hh/4cdKt9z08fHxpOe88oBj8WTfR0q3PB7PI6+evUh4F92o4idsPvZ0fdwGJ63SDs+HDS5tFqm7WecUF5teJ65oDlxpvlbdaUI6HgYY7gJ9/cUlYochE+bxvKDD/zqz9vj+V59jnfJ8vfngkY/UOh0+rHTArKVLWqj/0TaiH2l3Nf2GpEf64rL89PGMOVMsp65IP8du2GjDwBe+lT6zNL9tV6UtXSL3DGjrZKE+fW1fHVYxmr85qubCeScIrCvW9pHDqg36o9kG/dAhO/bR0kEvjKo6tH3sfti+sNr/APXpk2sT07skr1sLOxEyjbJOr+CdylrEZO5YvOvl03oM+nw7z+eLGHXo/bOSG6LX8wzY/2LrZ1RfcoXyX9m2/tgB9CFhfrD1TdfIyCyP8l81nxC39SvTvF2zRyg73/2xsvOd+aRCl4qizf3uZ4yUvqj/ZVy09+v78SuPxvf7Z13SUATbmvF2J8G+D70CvF9sBBOFe2oI9r8pRHVoqS+7puyUSOVgZfMPh83fKIb7NWnzD/A3Jw2A3V8w7xLY/VNg87c98LOGMdqpsQ7AvAM2fwdwg/Y/z03Tv0Xbn/6tAZZ/y96jWC2GBmsX6gUa/sv7dn4iz5UER8LW1wfDHmpXdxa0wY7gXGLASQ/mczXoSfoDQFuhj62cFx9b58+Z84JxpuOPk/PCXxosvdWR8+JjK+eFXwuSPhjP8PcPzRWhxHgMg8uKYWhzxDDs1UtjMteFFXc3VnOtCm2T+7Uqt8UrKrfF6FmYE2A4ROa2GOJPIb0/os7FVOrerj2/xPvxVl4Lv8prYSyFTTNjRENoLfOao9zCZba7djFs+R2KXqi/8bwf9TXqaNTfOq+H/gq9jfxm72kjG6gDPAw6LZ8qiriWJ2ItG8SJ/n9gHbdgHZvnjZ0XxjruxjruXIx1FGodNaybhjXjel6AdczjumFNmcO/nnFgWFOxnOMeyvw5QQP/uW5cx7VTMUas1R9N++zpyMiiPabKEyRywPtXraxzJUTadtu8P/0Y3s/4il3gBTd/qOIrFG9XcRP/+lDxfsZVEEeX9/gV1Ps3P1S83/jov/P+qtRjef8dH8bPApcI6Phtx+exp3zkOKsb6s1jn/xQ8VjNVLHAfXWC/mSs3e6wj46vc/zearcTa7/nKHmlkOcEpG/zzyqfjsehh1KObAZfoUyS+uhk3mdbGA1bsuiSPNN7Uj8+DXss33zo0Kcbes+x2hrLRZbfZD9wIRO8/RB4+2bGWVt8nfsK5OHzpvXjY7vC9J5COQQ5m6AztiahkT48+hjpX6RvkT5F+hYvtHyL9ClWyTuEh0rfotOvSD8ifef0JUo/otDOqbJ8ieXp4MmWL1H6f1/RgsYQJa+vSxTDJoK30C/S316APtn0fhAzR/TnS22/0vQu6vr//Vxr3/Os12ryPFos5BJNtPVqLd99CPPl2U3akG2QXR25yQ0Xny6W08/SkXtJg/Q9B2DjyTj4BP9u/Mm8AZZtmFwsvG3g+9QnQjKGPcHP9vlubrfca5wD/unlfR97MI9KTY1rliOXqMhrXlmteX7HHIq0hew6dg5Rjp1xyLRBE/ScbfTXfwre0d5JvX6kf6YYKXNhXeerXZldKZoO/aM0uAt8K5HniT4wV1SOib48zYF7m8+A3HTkJ1A5/0Y28n5TdZY5s+AC5vyTcYzg6zyDSH2COsdkdSdiyMJD4uSbMTW2sCtnW1unsjVoZ635OW3wEY0e6l6omwKeyZxeukjxb+I5gVThv8Dam2+DTfa/4qiNnxd2KZ07TzeCtengAX10b6MPX+jUBzQ69e+UD4+vfz/wgaLHnTyTwhxy7dYeA+nB9qFD5osk455QIuQe8N/2nW8hPwaMvmS+rYgRe8el+6nrJWm6/9D++L4h9ww7Py8NkqYPY2zcC+uy9pveisZtoFLmRf6LeYxfk7wvdAFkM3gR6agUNGfvV5VZ+7LfYuzSXyx5hYj9NHZ8/vTmBw4b9i+9+VO5BY9xR5QOSX+H7ecgDlwY41ocS89bXzC9vL9ZxgznA8Zr4/lNnv4J4+StM7J1Kr9JEspCW60z0qDVh6/Fcyu+uVQ02XpFR11iw1Ot5gr9Xl9LGPoF9YoQ9AjqFXlJW1d21E1pEG7XKuv8zLbwVusc9I9NSYdXHYn7LBaVCm8J/s9OM71S1iua3Zf3M9ObBdrbr+IF9m3meTQ9uZFl39CHa61FmlMOlYui/VjDlu74mUDal/FY8axIeyb4hW7HisOe+9r0jpBnKUdE2r5SZ/hG/AAOcz/aicM/+eD4OPxRq4XD9McBj6fJO9CzGplDSp1/yozsLcD8xYDI2nzT+2WJwk3i+Fd6ZiNx2Mb1vjhKfCZuE5+duLxJpES2niK89G8/DnznXvhp3LsHbM8HTtdPFE3MA3m3zrySOY1gmDHXYQXjqgoF8z9w3wk4NlLqyyP9AvJrF8aUD12rR1fWtcY86F2fYnwGdOi2xb11Z+pYhrwfBjzO0ptPsvRmxmFR56qHrtUMmeax9OYtf4nbkqQ5yr6f8N7T0Yq3ZDhty/ze69IOGHFdRljrsr+1v3VRd/X8ylqXdrS/1iMKO2GPjThi4dnlCgZXW3hXdZl6vsp61qaq58ut59WXqGfe9UP/Jv2ZTv8mfZu2X/PgS4a8r7MnP8BuFXsR6pTnY+W5nPprzaZdwPMH8b/4qOLrtt/zqTFivdKV3Y3S30n/qsUD3gAvtnOq5e+1zg58pc4OuPT03mcHImrfz6BMs+xzCUd7D9vBk1Y74Fja1JsnnWjB8QnAjnFN19OfY/tO7+W5JF3iMPNGSj9qmxqPM+/blrAaSxtwcO9pP2k4aNH/6ikW/VvrUnqRev7Weg5foJ4j1nNtuXrebT3nlanndntdDfW8w3quKlHPnzOPY47FA/2OPAGwozY/hvl+rPTRxWMF70CKze2qaZVnD862cgSgntMOYvxH1fDmz5gfgPkAahIw1s+N2EysAX2GHcyd76tbuVXGB2v+Upkb4MlVeQv1nrh4mSduHNpPal4Zhk5f6ooW076grfeTpb6V5QXR4jIhvutgnjzYGLQ5aG9c0WKucFk2BtdpuWuk3wX9mzSVzvOCvKPgZubvHCrjH4bJM0nD/Fc7zrpgvJHKj5bJuAfGWN9m5UHivqqkSdh4ZaeJQvucsAu6mbT3oGfVLzW9f0wQcu+0Rh8pYSaW8qyVr4VxZXufSWwQp0aLO4AXHD9smgLn+E/E+Pc+M6XBOQd+8/6Hag4jZV6ZkY2sc6OFJ6XFah1vwTpSvj+EP/K6Tw6pM3XhzqPyTJ06P5fZc7Z4Bnjuog+UD7zE8oE3dZoj1u4wi8gPaPflOOTI5l5yJCOymHs7mi1HwLt8Jn0V2xijNNPH2FXaayKdbTllivSh1sR9/sy5xnmS5iQPmz1z43mgK/Km8vvMIo4jdljFXJJuFnVbZzutc0G8+7fXfoR1Luhz8/h6xrMtx7fJxrYomnb6/uj3+yfgO545Y6YrWyd/Bvo5qvZUuY70VV1PGpZ5kxIav+FZctLhaWp9tCO2zHPLfKP0BcjYjVvl/XnMRTCH9G/Lu4NY51CrQ79r1YLfHFZrqrWoNXWekax8/6g8I5mruyKzsJZc4xL8TjKVXtEK/kjZFMN6JAIfbZ/CQxgneTP5NvnzXsf+FPm2zcMfPRqHp3PNuF7bATPqHU1d8bb2yvNYCf22Rf+hU5fyvq90KfpqeM6kDbqUPGdi6VLyLCTGWn9E5TukTk89gXtzbJf9sV/2ZfdRDx2HthDvIaJcOSumxmbvwTnllHNseTEF49qfmQ66cUeetuhm5w5FOzO/j9MOc3uFumgjKxn2oH2mD7zxZ1ZOINh925hblOeHxcI06+ywHXOiaIy5ZNvBP2/BX7t/egPPDtvnhon7T98m40z9Ay0+lgb8xzf75mbWrSwVAyVPS5U8LfX4PM1Ma6BPirhKm0vGgoAX2bnCjmw3Vzyv8LplNf7zbF/nJhGbxvo3q3teZopBzL8UG4y+ZonB/rv6OdNZijKe+2JfxmGVI+nXEod69xfernjeVryrv8ksngU5EYNe1sS7nt/jGTBXpA1j4Lkb5sUlHHl25S29T96PG+J8uPIGlffjjwnlfub9IC9u19Td5Pb9QbWtpjfzcO+z1pfMjLfBOFTOexjzeoEXYw4TUqgn8my0fe+V9Xd02ksN07dP/pDx7DxDla2JdfIM3CgxnPm2eSaOdqtAuctbGhP1KQFDlHw0/9bKjR4r/r3yDFEk31+G95Xq/UysNc/Y6eKhCr2w/g6er5uUOHqVkQ4bN1WsH2wsaRly1pKWoeh3gj7YX6wP8U/Uh/rNGvBRnvG2+vKgrSqXjDmflKeLCV7QcO25Rmwz7JvKW+s3euZVbqzXohOG015/3xGLWyS8rNd33PY3vJPMpftaxuEb46i5IbdS7GseIrxsn3ujMqedS/G5t1yqLU0TTcdrzzMoOkGYKofF6qHC+8Q4MaHmEW3OQ+nqfMSCRDHM2SbsOi/xsUgf5F+DsjWXRjfwnmedfuRyEePeDuMF8uhXK1f3u6y+FHhQTv41ovGbU8Vy5u/ISzMCntSrJ1WmiCKZOzIl+vJAnoPV5X33MZ79eTCZdhNzCYlt6/DdxYCVNwu2P74NwzYpnQj9JF3mhwlmyvtTf9MiY3iAd7WuTP9HwMe8y4xHcyGD5RmbBeF5tSdHi5lfrTZBvL/oCuNRxsBdIEplvfvFqYHR4sIAbadZ+D1mwQ3R0QtmRZuEaJgl3MxXEHzyIa2hnXtKQ0VwFsavnyCK5P4VxqFdyfFr/vUYq32HfN87745Oe/dpxlTu2e5Y8wPm/7Tmz2+Pr3nV98yfM7VB7u9uNYIhwIDnXLjvu8il+dumqXyqt8DWTWB8uZ4g75Kw85WETlLnYgDSbeSPNl8M7TWbbPg+wzh61GE9uQcCu3UxxrnWpfDJiescaxXGulmLFpvXC5kXVuY3oN8Y5bwvr/0lEeyo1ubvfc+6e513eNxeOr/yy8Riwsv4AXilVMozNRV5eor/KsDXrBnY0Jd2bwS99YXhTIyL55/NWSJ2Mr6nzfCX78QkN+SoNlHFN94/b+bGDoytHWPj+UYPnuU94/V114VeUfcz8bv2Bdp8xtoKvOddsu1+bb6TNpLAH3toibyT64b2qwCDZzFnxg0678fyDQLuvIK1AwyEEKgXLQ7XlM5fLUSxj3cxPoLyI4kTqNNBRyGvWqpZ85Uw53y/MyaBP08gz+P73vhTuZHnvMTQumzyABd4Gu+pcIGvCXf+Kk0kUn4Ffaf033Yu4ESeEoFcgJ4iz3Od68DbPOY8WOvqOd+RuF3pca/QZ3+csVaCvzDXhxyvUOfQnONz9xqfW46vedzxx2fji33PZF+8yR/o8tvnfS4Qun8WfQHuH0Me8p6toYHF4srg2lOZ+/jKYPk8MXztOCFjxfMWVG2knCpdtzh7NcqSf2BO/y/wT+o1vyQ5v8rRx58f5+T5Abp4+1Pua2ZuI78L6wMb5F10NeQHWWO5Xv96zxHHkCW85SWSzyx10u4NoJG70Z/NZyrn3bDxAnznsXgNfdkhPbPxpaPqLsvV76DPPm3I8Q4Vk36OOsaZzPXI+8N9wbZrRCxjnrIBnnmvjw3gwJ1T37POAvbTrsx1grY5BurENn/KE6nyrM3lp4jlV3Nvuh8Yym8Bx2brjGh5Qu+8TauHCe+fzzgWJrMAE35PPmOfm3oyhXl+oBPPm7Ux9JK1BwKeQTpfjLJ28AqbT6z7l7mivu9Zqt1mEWm9/nDiBMZQ158h87gEBeBD+4MwmumAUVWXslMIJ8LoTAtG7wIXZT578O5wMfm8FrmEZ4OnyRigbaHEgQ1OHLj8vd40u/ZH/ePAgj44sPVfcRyoOgRb8wy1rlV673Ut+oF1ffFfjnV1rA11Iw9opzlVTOiPbpgzlbRjwG5bNFA0EV7UJ3geVQcN8TyqtjBvlSH3/q0c1CnHpyOZr/kls+nQEXm37PDmk8XyrRY+5+218LnPd22JUxu0Ja6GMOSrNpF5ITIbvz+icjXL/PqW7CTv9zDmtlzEjscjRHfihDKLR/SWm3EekR8z1/OcVuodS1pG66nQo3e8NYv3EMEe2dtE35Zr2xqXiD15hHfGK32H9qi690CPhJp4Bz14nFvpPbbOo5nmhHaMrc6aey3m3oG5k6cQh8lXXlC2ZiN08BElhBfg/cwRlbtWSPzX/MwDyzbn4Pu/qDt6h/8Sv/+Ib2YeNZuo7/zB7D9/xdFpT8m7qGm3U7+280xQv/ZCj+c91O1TRXDCv1SeCudd1B++a67Yxbtr+8B2EWB782DuGZVSJwvuBo1VfTdk2CE9sWDMQmNZHWzGJbn0jan7TjuBk3cNFVfVpKt7/2YuEoE/33dvqwY8Zdu61XYl2vah7QtmV0X1VCN2w+y8aJ5HBBiryb3GvuN4gL7SA8DlkWLC/nJ3gLaHeYD8Kq3xZYyd//NcvooZ/2Je17TGtnLe74tnvFPrqPp3trmMtAibLe+DKbHQMi1wA+Z5kmD8IuzBf8l8HQWhFFEYLpc6Rgt1J+g4wUvRZmWXMclIVnRFf63w/SjgOg+6eo7U23rh32PAv/X3rU9Zf999rcbsuzb6sqPFfcdCWIynDgUcyh3afL6Z6zs/AXhX/C/H/j10n5ngK+GtWoDtkIe89K66s4n8Iwx9yCPvPoJcKBaWb+guyT9O+ldf/qH1+IbWvNu/XPA55EJ/480F/HOjYlKWJoraZxnBqixxR2WGOgsjRpUuo3731UDhpTx1ytej0z6VcrUHdtun8M6VJmeckWewKCSsOfZDGJ+GsZdQvg6X8SrB8GKNa1JhvivzsBSQvpsZk+hYq9A75gp7XIRd1ais4aC/glJdFEp+6NBr78d8fFHwkCFiAmHItZw5WK3lAAsm9dZaZqFt53rW7zMn1AEWdVHio1YQTlV39HDeW3k+wQGP5zoVbjv7Xoy+K9E3YNrT9xplTy51W337+sGj0NfmhBr0W4N+16If+7dtvyu4u4atoSwbasRIN/Th7QSN7gKNtOuZBfIeOt6JdIrMRxlbBf2y+XuzaPcphrLv/cA30KdoLvKXzPNEx6CtC5KgFyy8t7VtlbuhfYYIfg84t626AL+hR35nNhmpItZNfuXSVE4B3dXYhva/Oox6aNfYZxaV3V/acIr0Maox7AJOc1wcy81dYtJu8CnmDLmb4/nWlPZfJeizCOPYDT508yHMc15R9O5+dEYnbhIGvLPEXh8+V553cevPGGMLfOA96E6cmY659G2vlnIU69O8N7FnfRZZ66Nb61PZz/pUwtaIgsYGoI8S9F9i9X++zb+TevPv1JsWtZizxm0jP2beof1WDiJ177gosPMQ0RdDXv76Oyov+swU+v7F9jyRFWi7mXebuBrfxrtQnfSXLCVvkvlk3GJO14q67K5ELbhpsJhTn6151w8XV1WCR1+L73+Mv7kzRSDjsiJ/1uiswEczswIjMba7f2tEee8D1qnxpXeUXSlzU+QY97AslliX/ZxVbqCsC881roxIKeiRfcVyeF+TW+qR+1HPPAw7mnFj5aVBkZo+PNdjzAmNqMsOoVyIJ1pOfkflShIurUlzg297fC1XcT7Qhzya1kT+Vq/RFhGxA7lacLgFB3uu5FnhBWjrVHmXE2TmBZNkjAH7YDlslUHvqLvFhc9X0YW5jcI3mYm+CuZ9GIHfI3n38mSVo9VcBb3kJeomWhBjqQhtEMEDD9AnkBo4mFsaTBOLWtJFln+uK2tbPHdORsET6KP+++gGYz/tkix/aL/2YuXVj31vLGxepXdf2DrjVbFvLHTjUGJp8ABoIIFnJfTsRtqpoUfQX06pPPccRT8j5b6SGL6rmjY0+jZFsA30msk8Bib0shxRGKoz5D3K9GeWYS3LfFmBg1uTApqHse4Zja9uo5zMIE5V1L6j+GalHp3A8+eTEkUgayvjB0ZGGsCz3boxdsA8jsMI7tfdBSHeq8l+slQ/zT939NPcu581jn5utvrB98XhrQkBc5mI3YEyxhO27zdi9Ft+9QVtn7SCA9Z3v+daMw/CuVqxeK+0gbSfMcKKtcea3OXK8Ne4siMPvovvXmL8yKjq0/8jvIsTxbA6Xcy57Z/C26HrBdTbXKlGQ36qaDjvWVG4KFFcVTX9PL+xUEv7Kf5cXy1srUwT/pnVM6M1LldkLfC1HXPtxrfjvYI5yb5LAz5VFYAHHjKb8oYqHE4ZI5bPLeAd90PncJ/VBRxa1Loo+55FQxtm5mvBNUIUli1c2MqYn8o17sCJmFfVcPXtt6PFcsKaMLfh/fQB08t9eJ7Lb/PzDNsI6nC8D6/gt+O14ijwZpZb988D7lRhzNcu/GRVlnlha1Zilv/aoVlyn6ghwviO1ADvt2COrgHo81ry/RTYKC769rXqWxuEt5T77imCe45zngXv+fEAkX7yKKPhplGiYeZaUXiRW1ylX5nv3wz4bMHfyehPG6r5E2bfFN0BXe9pwOjGoaKB/Cu8+KIGuc89WcUwjRDp/jo9PbLlFLUuJbqoLrhHeEdjXfB7zqAFx67LpMtEYb5cl0lyXX7SZ11miHTZJ9clhm8Lf6rWJR3rUos1qP2FWE8c9ZwBvFxsgI5GFuwFDnWCDr9UuQ4KeL+e59ZocWgV9AYZQ64NDIGms88XRV3yvoP0An4XY/5EixaiM1RcaPIQTdIn10rmSQD/SLNpQx9QkOZLa9wL3D+IteMZqxjvvpDtjSrYuVgEMYHYiXcaz+UmNZ//o7vEc8x7V5LsOx9tVz/8uPDmWbAZB135HbdIP3Jrx3kzosZzF2QZsSO31p93Q5aIQaY/N+lRBSdPzcurCKN2yKQx+N3mcvt33npDdJNIi5zK/Rpdx5y1gvPvNZ77UXLz+Wn3i+i9Pt95kIXPMY6q+e/KNwT+Usx+T99N/nPV2C/bxPuMFyg47eVVq4G/cn0ZjwaYCZ/WuB84yfzG4EcFUT2lkXM8qCc3Vll+udrRwnvi3cZz12GMuQObz//7r8VzIgd6fULp2PpsEQsDFptSfOdXDi4bSxjeuKi0gXb+nYvKGhjzNiNRzHn3EeEdoqu8q8zvRN528SgjlrBwwireXZ0PHe7mW2+KznQl+P9y74RVX4OviHm50zXmF0KZiTrJqPOzhcZzPwe8pwCG9976Fzn3RMBxhq5VP3e68J6M9uoHQCfDt2yLbc4Arj4r7zLWCo7XNnPi/P3XxnObUprPP/FO8dzqbOBIku98DW1L3nsKZNphI7jzc+jexMdimfO9af+KwZDlekEI/K9T3veo7pyV+SY/Bx9n3nXwP9bXYe+STxT901zhyY5uENcAvz8Hj3tIm3P6LbwbJY36UuP+FeqOswOyPdF4DeoubjeLQxvkXlB1yo9VDrSZCxe0juBd94OB+9eKwu9SVB7lJxlL6BoQ0XeY3lyXm3cTeL/T3Y0dKSL2NXjGJk3MuTwR9Ir1DVx5ut8nSA9DI08nCG+Ja8d5zw0QV30NPvKo24hFSrKu+JJnVgeIOQ9fI7yWT7piGNbvrSQjlrhw4bJcbYDMV/Sb2TdHNcD1t8w9Adg+sD3f3wZYz8B7np18a4zRsGeMaNikadWXjxLek/At42F/S/8OvvvN7BujGFv1ZUfUWtnfs022x3b24N0M7eY/1ZyQdYUpfOfPcA2NNIwUXs7hO3144/eY49lltPlRHoPND73S/a87H2Ve8ts+lTRUUIXxLxaubR1Yo39hLZjPvGMw8bh/nrf4E9Nbp4+IPDF6xUrS1defmd5K8LQqXeW3Zb7yXLHjvEnkdYlxmJUA77++QsWx5lswexow+62EWaKE2c3VN0UXYX436gn+MszxptbRfvLDGXhPmD0NmL0FmJXorurncoT3Inx7A+qx/v34jt+X6G4Jsw7dVWB/zzbLJMwSe2BWp2sRYYj3nxhdu5Lw2wH42XNIpq/MwXtLP4jLxAvzxfLlBdybj8vEfMjEJyATF0Em2vLQB3l43dvmilpLHp6G7yT/boF+4XfwZ+hdXc+IQvKXrHbwJrwjfyKvaf7C9JI/HwBvZxvk4eT33RYPt/k0Yxtu/mfc7nVnTb3HmEZdg/I1rcCmH9ISaahzp7me82O7bJ/tumCb2u2yDzfmPnOAaGKeeOJ4mcwV76voAC/7IE8s555Ch8xjzzyP9d+HcrTYoiQj6ILNGS0R6hxrNe8KGFXAO9yZU1YMZO72NPKECg/sirTZd29c9kh0wvIE6DMuV/Ui5n5Bnc7hIuAxzfXREo4lB+0YwcNSfsHmxLjHX1keXNYQneAxBgXS3EZwvIbf0n+q4PFbxnM54ME9OpWvQfkB6t+2zgpCb7htt1lIGnHh927YjOMYdyJzTfbofesob6ljUu9T8jCjcfTbcd1vD353ko8mRSf8kGz2/exY2XzdC6Lw0rB4f4b0mbka1xxV+/Tsl/qmrWsmOvp7x+rP50Z/fXDps6+BX1LPjq+tE2d64u0BJ+bhaKMvVB/QSF7QvlUEd94uYpfRxnGLs3febsTatxrB2g9M752AC+lmF+ratEO6If2Qds6mfQm+TxuXuu9LbyvdN7xfys19466T+FhQZM3jPfw/Ho8pOzuuV13687hedflZx+pV87X/Ta9qPMJ4CXcBz/o+zTiUw7wTGzo3ZJg+BHQ5QRTOZW45zqEc9tZa2D7oi75x3j3Ju+BnuTKkzML8gg+8BXt9aHRD/dWQW8uU3Hp3sPAeWGsED6KcssdTKIoz0LZ7iBG7KyUqZZY+UOb7qC74mZJba+5b0JoGuVVFuXWdKPwF5NZMeQY9NTIbMob5DWbKHIwu2L8idgtkVokls2aCZ1x+5Vi/IWVWqpRZm7Qd542FzLoFMusKyKx94L/fkf9CZj33U+6l+yp0i/8+lUSdY+Ey5ukk/70Aui/ly4WgdcqYi7aTf4oCyk3y38ZxRsM/x4H/QmY9lym8Y/BtJepdyDsK8d0Fs2+Iljhklv29LbPYDvlvruvmP5WcqHjuDi01ksyzIJjDV/rgxl9ijs+VUmalSpk1EzLroXchswCHX0yAvTZExaDy3AHxJu2asgbbTrqkOG4nXV4Zt5NOrzoWb7rL/jc76WXeacOYLqy5AVs8hnXf5EqLbPlO3QNMnCBuEC9ceOf71nzZ/XYfXox2iBdXf6v4LuOfDjxgxDLpSwXfdSWJpuoePjtQ8tkFHrFc6KKoGevdk6MJPLYe+L45ReFkGvUP8NHi2Xdt3OCPTpgLPsp8duSjrLMefBS8b/1+9HlXRXnwIOuUDQrMTTCCrQ+Bd6Bc9u8WTZU9/QvZ//Xo30D/tm3o5POVGBPHUZVCmvW1ZFrjKAI/P3hSdMJHGMcOaxys09lnHHed4hgH6odBF1Vor43ne92+ioPA9fFJ9au452UIjA1wXb9IBAj3KlPlAbr+LfKRrMafyP85jde8RX94eiP9JW/9w1xhx0wwDxX9TX33PM1Z4/z0RSV/bRYS384E/yJv+4l1l6pcc+bSngf9Fs/k0dI/Atl8gLGblj5Q6vlhfWDRJrPIBL/h2TjqwOQL3Dtc+5TpncI8AMI1jPv/nFMVfrejTt6eBa077xaxj/4h+XyjeMhkLosgYzNcQpvqga4bQnuUBWWou5H1rlGxG+3Qoem3sXXinXdzjZReXPWUWaQl+SrCgwVsHV/LTuh87K8NfS1GG+34hu/b8M1O6IGVs/OjbO905rgBr6+zdMxb3jS91C2/flYUUc+81X4PuSD1Kd13/vxnJe5st3WovN/FdagDuQpmhBfhVAc4vcz4SvAJrmX4JcAAvOUPGFNlo2ii/8qWAZf9xvRWtU7yF2MNnHroc7/trYcmvWgeVw99t0B48x188H/VQ02REpnZRw991/X/roeynfYf0EPf+y+y9h+mxZM+VzzpA8DpVlPdX0s5/tN/Kvkd3ib12O02vxlh8ZtFHWbTrT30niLpfQbWxLcDukM//CYMGmZMVIZF5+Nn/3pjGnSP9aDzTRads85HcTrfTjq/2h2n85e+oF/Mkf8DYxZfmC8H/+E40/g5z/PE60z4h9LTPoJO9Pw/+ub+jdcbZ9Xj2Bk3/KSjrtZtt6n2kPOsup+h3sp+21T1Rlj1yOveQf+POMf5We9xplp1/4V6v3HUC3/Su2+XVW+z1PUyChZrrm20v76CvnE73tmy7atyJd9+ATusr4xLeht4o2dErhv92Eop22YS78+z8D67x/56og/e1wHvTx/bG+//ArxfAtzdIWy8ny3xnvh6o54kcdbGVyfe1wHvT0/oH+/r/ke8n2Hh9XXH2F/Ztv213fZJllbEecfOE3/YJ/lFF/U8V+O8wzLfaJA+L2VDKf23i3YAdN97u+I0NsNBY9dZNPbvPnKg6z2lV1OfZnu2L402mNSrFyj/+c1dDj1T/tYa6Uf8lvetgT4bDys+F9a1IO2zvYw9WThh1fVvmiv28nzk1aKJPN/2lz17s+kdPWPCqgvwXfd7gxtgAzWGFrsDafTbU25AX2+Dnr5YT4MeMkLqIaE3oJsOhm46GrrpVqWb3naq8Ha/d0VDLvgsc9hRh/0Xz5JwLJAHbVsVz6X+3wF5UIzxUP/vgCxoQxviWtFEnyrkTsz2q351tenVt+f7Ob8NXcfKgJHbzULCddXRY3l7Ltqvv0Hx9iSM4y7QWaXMhadVp2Csq8FbqtAP+Iv0316iifQx6UbDmAzRsD5PFD6ZIK5KvrLIXwu97TH8jbH8t27ooDXQZ6m7jU4WDaSpOylbINeqLLnH+IUOwL0NsvwNwKptyKUNfM/7B6TMA/2dSBvhGuaEcw3rQP2X8J9yuR3ffIdvdmLcHahX/4zZRL2espj5KUEnU9m2gOzl+XzK5+2ovx8ymTked17DvmFX8Wwc+qAePMPSgxteMb3Uf2+5UBRR76U+bOu+lz9tenmW8LY3e+uWoZGMa4V9h7V1PWaubwMO2LYf7MkC5fdVuP/RG8r2+hXaIH3RLtRtHfS3ZtMNPTLBLWUC7zj59ASx3PMbs4j3XfbIhRUiVglb3+fi2TO9MYp6baQztEe9lPY95YGSFXdt3J9v2/hxWWHrpp3yXmVXAfMwwrbfXgTb/rFzohOKYNuvh9y4uhZyY627h4e+gDnU+8yXT3uzT04VR52n34jnVOmLd7WEwbUK72z7YFwddYrz/K/GFA6TH1xn4fAXv1J6TM/+yOlxXrTlBMWLyIfIf2rAf5rRRi/+XNSHP39qHpc/3zb4/3/8+Xh6yf8v/Nmpl/THM6mX8Kww+VKdnha5+HOzBzfLIuYGAZ2NObC7YBsy3uFvb/Q9xxP30RRbaxgGLrsGGjIHzq/J07EW3Pvkfbrc98wbiv/3K998KEN4bd5MPm/zfFeM53q0RvID7tdLnr5V6U6/QT8fYtxdUzkuXfJWczF4Ouice5G8o6YNbZbrI7fRd811X/I6xjYgusEYBv66WPHXQWnC2wW6joGuE/vBo+6vFS+8zzwWJ79Ae8bPFE4mxxRPJq8in+L7NoytFXXIl9rIo34qmsgfK8GLbR750MemN3l7kZ9zZCzarDf62KCD1fjCzBuJMW7OMddTJyS8t7/OfegR3MttvOUNxRts2zR/mdk0u4cvJEm+8MEo8ITfm71tU/CE49mmncN+0Dbd/mvoihOGx3XF6X6z+DPgxzmOOfhSQTfjuO8uvBx3VM9uvIP4VMJ1c0l8OrkvPkmeoPBp7esKn9qAT9QTu0qM2OdH1V3ixBN5xow5a+aKmO27s/128k7ly4WX97KEoQOIZhEIQ+7b++8yTyfwRLghJ+eJ4eMxBuafZ/3JWM9JOmgCzzP0kZGnvzZ7rUN4v7lhAc/qz1D3adn3ZvsSRDFxiz7CK2MWzi5WOPsJ5iJz3oN3/hG/aePacUe0dfuzc7uKJd3Je+iJb8eju5+83kN3jV0Yx1OQ6/917/AicczeIXUhe//wu2hcF9tp+UeVbzKj0daddqJ+Fuqtf72/NVTnns+xxka8+wXm3+iom/eNLQNUjtdTrLrVpG3H3P+v3/aV3Mh2zJ3yh/OnDCq63Cymf/b3r/dnL6ixDXSM7U/gU4sddavu7G0HCKvu/6HefEe92rm97YpDW1W9P5Dv/Rfd823eTWu9k7jg0HftNWlGnZ85+tN+Zfaikc+s/u5Reb945mI4Y1AOjncBJ/GHsT2MOrVox8zRghfiP30n1FN2dEnevG6UxTfa0symX/TwjVTJN97MEcup44o0s6gWPL3Hp/S5gJ4lCn0DjdhB6mVy73WE3HslH+EeIvcLMmbfubFooM1LNMlL+M1ya7/g4FRFy53S5+7iXsG686BP/HSI2isYBfo8b4hZHNWTJS5kH7OeCT13Ia6wYMHzoL+IqrnZutIi82jTzT1zS1S60iwR+30O72Y4yhjBXvsiM6ErlemisGsr8/tnNUblXqbeeAC6NvgA90cqYuA39SnMsaHmmj577sYPBkQndCYwl5PaG+H7udZcD9xu3TtOOt3K2JWRcj+8E+MMg5+G+S34aSfwd0TX0WLO9z9bHTgZO2rRvcLf6635vtHJHA+ugr2Qf/zm/a39wUjh8RU2jKbzzq0RBVxT5prqvpt3BCsZv7nv9zK+SuWX+NFWm95GFawB3XTD1uB9gN2z4t+/sLU/XqXW6Azr+27Am3cFR+W+fXLjQYvW12w9/vrm9vTNs67ZjYQlY+y4zrafxHXgqBWryXXWZIxoBtbY2H+0KJziwF/IvjDzbGB9DkpdOLsgXe7XgQblGqU1pvXg8NyNjw209WGFwyHHuh4Ez9kvvxkp5Q9lm72mq4fE17T4W7WmtzjmWPvN0V78ctcWNcdfdtIOhYwCDyEf4BliFX+TJmNvGI91ckfChFcYY+XA87IdR5tu6cHzZIXn0Ek+yBbLK/8DPC/vjedVwPNawCFaLuQZX9oGtAtsfYDzVLh918Y7B/Sm45ClE3icNkG5tAnWcb9v/wBlE7yEuS/7TM29wDH38KdHe/HOp6y5v30I+DSV+KR0hBO2Hp//r9xi6wijCri+3eAnf+jRDdX3g7b2JwMUPv9uS1zH4PeU89SJLZ1X4uSRLcf3Y92zxSF7yy1aKI7Twjdb+hu7wudq69tu4A/xmHua9M2+g7Wn3pkV7Y3b+f8+2nRjz9oOkGv7c67rF31wG+tq43YX5Ah5c5fkr2mSjxHPnbh9MPEHcNvmV9U2v1K4fQC43ZSkcPsA1tf7iVrfFx3zXf2xza8UrM+05rsB66v0wRGNFbCndwHH7f3NToyVeE4fTJfcA00vIO6/+U7CBFuH3BQ7ljaou7A+v+2hj20JE7hfnIn1LzykYDoacnL4VuW3uz7WG88Wb+mP71nyvx88ewlt/9o5306z13z3b7bm2+fsMv94/x/PjstciivqsoWn7jrqfD11+sbfph8//tYZe8u4U8bfdmxWcaqVjjtAo7eL4H9QTpgRr+zY9jEWTtF/yTtGGIP6C9Rj/HuaT8adVoxSvuSWHNpXi12BEWJRS7YY5e90jdoWut2w7iXIbkwAPCpHRTeEBjC2dZQ/NF7EkrovaD31RNF0CN+Jrxe2fjA8yU8cop/0szuMhp/qo/wz9JzI27B3cvW06pSRwpsCOz9XV36kdx17gFkjRKELdjjWpoB7gNfiL296np/7gJ404c/n/rHuiiw+anqjekrBub8SDaGuKXJPKuchEfuoTAR2uNIjpYynGq/yY48SWmRJlvDWJRr78njXM/B83WZpU0kYMSdpnhX/n8t72lEu6bGfPbh7RoIe1R7cuh47a5qIaU9PC4Zha3WhPL3+R4EMaw/O+HxKTMVV3LVxrm7vwyk65Dubv7K9NPJUt9wDXJfmLQ9OR/1ee2bpx98ze2dzH9ye5erhYZdYeFrrAg9h7kZHXe2I2avuj6y6zAO9wVGv6nDveoVWPdrpNfqoyILRT6zker6bILynT5/o9+i0Q3Kk75v731lY07MSeadI1hXf6Df9KZexR4lq7zvF8q38ItmI6bCt6VujbyW/epbc+x7XWuA/Tdf9X+qigHvWO/Cee98zBxkNiwaJhlxdq76cOfMZrzVADDtNd8m9b+IKxtSz9812vnTsfbMd7n3vYLyWPjRCvXnB6KUrTfpMNd/59hzo+77nvTsfpQ/pOebzWmAEy/WMbW3y/jjujWY33gB4/BywYFtf6QMb7fbYFttke1+ZKq95Bf6znHX4rkT3nZ91RO15vkh/zT30RYxsrLpv4bK/NZsrfLpoIq3aNJO62/TmtU70M9fSFY41am5T9ri21/R2gGblfZiz1Bll2gwdQ9LGLkJ7qdSpQKvgdTJedyTKJlGuoQ/N0rekrrHTbJrVg/+6xP+/ZYnlvg7zWPwHzgvSAM+rW3SAdW1hbHsp8Jz3WuTNvnUjz/JvBl4/ofx8kg74/tJhIqBZdDAKdLDQooNRoINRYVPKnjQnPoZsfFSydmmzwscjsAm/nAKeZNX9cgrWkHjOM641RpDfsD7rLMY3fO87am6Q5wdRn3tQsWaHDnO4dz+/tvr5lDw/tc8dzuVueYezWW68fzweTv8V+XhXuTtg8/I5zeo8gJOX/6JZnSuodNznfHOzuvc5BD6/5k1zRbt1v/Hd1v3GnY3Vj8pYGJcW2a8PHtv5aO1K2CmRzvxFKzvvq2nlWZOQnlPwAtqpHxItpo4+QR/hr9MzI+Wgxcfx7dYy4/2wjCfOKcgX9S3/3CTPVuw7He+p9zHPWwjv84AfMm9j+tWTbkN7ngTKg+xtm826Rz9yaf6DuiuQKTL9aS5fS7Nr5LaYntTglI/qrIKSpXnN8Zy1PtD1+p57gNV74idz1i5rduas1frNWVs7QHgPzBoy9i2MezfXUs9s/Mg1wr/DNSoylrx/qxYgPPntJjW3OZdDro8DfnHMHG9sRlKDs//YJsf40E/f8e3bpMZX/b+MT6jx1Vvj8xznbi7J24EjwCV5R5fXgZOb92EeoO8w+pD7pxZOin1mk73GE5tVrBfzRNEfNJtxfNwPMXm2lH5Tl9KROd8hSQ1Kh/ZV/NvWZdxizunZwmuWZ/V7LznPVWTIs6W9dRPeT/7aJhULVzNYzDEgdzvfMFekD/W12PdxT7fwda7EV7Ed9kZEhDICc4GvjPGZC3xtRhvNkOk27j9t4WF68/KVPI89UqxuGbJJyvAinlVR97GLOSPT67In1WirJg38YGU38NUEb/JtNSZ5YOtLeT/UYN6bpmzAkudCf1yTMP0TyGT67a7ZpGiuGbzqo5vubT0J/f7Z89lK4ry++55W5nBzz/51tP4E3sE0oPH+WydEuzgGPb3xCfwPlys7/FP89iWJwmzqU576Fp4J7e/e8PZNSofjnbbiBOE9JMTS5pYpMc7bzuMq71RxiyKWa0tnxiDbm/S51v101hl3TRdeyevB023cPjgkfWyijd+jwPumlc7P030VJULcGupWewC2/huw5i0Koi//bVNvH7WP/E/GMGQ1LlbwXko9ZVlGdALhKlJEkVNHORaHsyT+htbGz1uVUo9uVzGIXx8CLk9TewWng0ZsmBEW5lwR5Lypw9LmdcHeLQM8tlwpigiLvFSxvkbPjrSnCtlGaBns/HZ5Hm1biUiLTFy6bOW1SbBt0SbbSbTufE4A3AZwLfX0bfSRhBcre5NndXcAnrUe4X3n71zX6IZm6LmME8rV06WuIPMy83wCxgeW4Wcu3YnXlgev09P9UdjD1rwil0FnWG/RN+fvc/D2g3+XZ6ALzpW0KH16LdyrJF7dBBg/i/JrHeugzcsZLvcVsRYlZ4k5lYOgRz8u5owbiP8XgE7xvzapvkVLav7eM6Z5ZX2KmMBxHugy18fhIfZddrLk4UvT5Xmu+NjndZnF8k6BgZr0L03a1EeXLKc9nCXl38t/t+I6pin/TpJ9t6SFiz7eMd2ucgzfRV1irStgXiNiK96QMq6gPhn0eo26L4XnJSS+gx6z7vVVOOUD+9OJb/h+Cfc/8M0CPWtgVuLjA/ktcwCJD5ZWeET9HdTxslp92aHbH6/wTKq/owbPg2AfEI+u13P8vC+2x3a25iicc9xrWnNUuu291hwvJi9cqM2pPyhjHyTep52q8L55iCj6Yd6t8J53X7+P9n7FfO+AZdvfe9NX3k5TwsAl4ejqgWNVhyqnPsP9L55XaX0NcJglgkbMLJoMvkmcqSzPDDz3d3Ve3BgPnekpI9b2POweP++n5N0IYk4eeKJYqK2Sd9R0qnY9nWYTvyXcQyWC59u2C19mgDmE5Lm+/9LO2IMyr21QwxrkYQ2EUGtDXZxjzGqtzQ5jPfKwHrxH91niBdb0939X5+vqOZcSmQOggvAmblR2m8UHsA5cn8cdcMoroK2eLnWSthpfy41/Z1wh9BDqbSijzulmGXS40i6zqe7WvInkyWHodr9EeX3MbNIKwasKRaDEJ+aMybrkntW8t2iUMdF+rjdNr02ft2Fs4oNft4YAozcsGg6BF53WD73eg/b5nnuIzR+ZTeZ43q/AHE1im8Z7V8Bf9r6mZNdtsIXC462zhFY9xh0uOarwS4AWGQsuRmMd8e46fE+7+Zb38N6iozdeN1fwzImvQBTx7hWuJXMdj2VuosmwgbEeGtZ0MtZEngfHWrShzbP+rmiJezmkpfAslQu3TGgD89y1kqb2CuYNzqkmHeVtX5VNWpohRPW7RxTO2PR0LXCyEmM68+9K33HiM/MA0AapPVF47yfcsJ62TGLsQmeaK9gxwhWsBEw8mCdjGCod31cCPyUPAJ8rZR4a0I+GfshLBfhglynvM4m8yzi6uUbQt80ssmUEz0VojJOGjNj8T1PKiPAAJSNmJcjzS41ts3i3fYY89334VSV/PeDzkLFNPWswi/6T6ITr9Cw/+ZzN09+B3DSsPH42H/nmNYev96iiCfIS6f97TfGRbzDmjtf67P0CppwP5+nLVvLL7uehv5vek9HPADu3jMUTmmMqP6aNC2WvK7rxDIjz1AaX4qmV4KnpwAXSd6HEhayC519TOFD4+rH8lGsPGSfXPqt1ebbNRy9nPgy57sK/rh8++lfHvEo/7s1HT7Pm3+TgYWteVTys8khvHrbwNcXDPJ7/zsMePKzw0TiseFgOedhkBw8r+d942CWxvjwsZ+CCxFUDaywetqAPD3unkzwsp+BnrykedjvnMlnxsMus8Tt52M0O2GgjbR6WJXlY4WtOHpYleVjrq/3wMPDI81/7f+dh573am4dx3K+g7Hd98PdHjjFWfWHlI7Lwl/W5fv9mzie0m4u6rcwrY83vTMe3qwf0nl/3q33mhzVZxTLMJ/zP+PzymDsAa+YmP/jn/9scdWuOlW+ZTcyVTT/EtcyBA55xAO+GkSdTb7Zze1h0xHs6Vst4z6yCX6PeeAd+dr2CNQWv933SGz8/eFXyugIx7L/jZ8NHCj8rP3Lgp1PGlv9v+HnLB4rH9Yufc4/Fz69aFH6uf1Xh5z9eicvYJ226c+Dnplcdfo5koXgX1oTr95Bz/VgOveA0lk3pg5/A18de/X/Hz+Wv9MXPrII0tJNmxvFrhWN8te7e+HVDX/wC/RMf5F2C/zkWv36Bd8a//9/GWG2N0fe52dTGuwkt+fenbjXe3Xj/IXEH8OnA74essTN3zmxr7MwBI3ljz/h1Of52rMV4aw71NoyhE7SgHeoI4a96zWEd5zAZ9T1f/b/N4VxrDpVfmk3yHAX6D6KM9wYcsweRefw9iANWDhD6tPvuRWxGe119/FddNSL4CvFvlQjWDRZzIFu99GXJuYSgG7+ibNNDI+qyPxTiu3pLhp/Us1cxoGevIgp737D64H7FCGu/gnsVZjFjwha1pOuj/JP0Udvo42vTR8o8GJ+z/xOiGyrtvYrJaq/i6VzRxPs/RqbBbvl6YSvp8YmTjYYH9WR/HfStsYOF13SlVd8Kufyl3OtX+xSfOfYp7s4ShW0J3KcYIfcprsFfqbVPYaQJf1n1zGidtU/RqacUnDdGNCwvE4E618jIau5NMGd/ubU3ka32JjbLvYnsxgcxbsKjuc++xJqW/vckrk5TexKwL77r8cleE9+T+ILnZh17Er4f2JPwOfYk2J69JyF/97cnkXn8PYmnXukvb5zSDca80ntP4olX+uxJOOqOfCW+J/HoK332JBz1hrzi3JNIjiwY/eBKrh33JK6YXuw3HHsSO7Qd53Vi/aYlGrGvS7Ku+Eq/6U9mgpjzdXLvPYlbrD2JEmtPoszak7iktcA/1bEnUefYk8gfJBpMwPPyhPiexFRrT4J4gTH17Elc0mdPos7ak6iTexJDIv+SexKPrNx0QtYVJZrvfMOxJ0Ec8YFm3AHlK8rprnvr0FdmEWD9XeU041Hii2Du2yj/nxr46bzKaCnqn/eQkOfwn3jvzkdzxajIpRHTu1gX26Rvd5UR5J7GWYAl97mnM38RxrJX7mmo8WySexqPrOR4vrD2NKbg/ya5pzEkwnczdN/5Iw6bhay/pmdPI7txL3gc9zXu/5u5Yi/4HPc2SNc2nf0C9nBpa7F/PL4Z4VhrI2ztbfAeHtA48zdRl7X3NtpzM8ZO/Ztcf95Z4efeBn1WbUFzxVhrb+MQeDVhsqW9977Gb4aL5Z5281j6sfc0pqg9DdJRMvUO5rDp2dO4ZSNtrFLQCO9/Yv4D0hHfj7X2NNiuuFLZFWKAoiXhVc+VO9Texhd/c9DKfyw7wsoL+RM1rw3f8T6QqSLWXieC2636jN3iN+11RrBUE72+s+te8jd1joF1BGXNFLXX8QHg8ndHv6WHe/c72eqX9VJTHpeygTLgI4x/S9eUGGXEoqHybERB12gVT0FZQflQNtQduLp7x5JW1EtOWdoSmjXWX7XGHbgzvzQ4b9eVDXcKUbjovoWtv8b6zB3uDsw8umPJJperuhKwY9vfoc8PzcRiSZPcK020ZEezHjj7byqvT/1AUTiRuSOxzh76dj0jA7/9G+1xsY6xnKJ+ZGARnptSReGAlCUtCXIcJ/nDs072s+9r0HciynlWNDTrFH+7aW6nP3yWLzewBO+S8C4061S/cBsNocQBDXUYSwj8wZcirtIG47tZ4PepS1o8V3r8u2ZpgfCsfP/+ci3A+Av6eyG80se4Va578Grv67NHR/Os/Pa8B20tZMUYYcS2zJ4VZf6HBsgKxmmwTn5qTcMNLYX+39xnLFsEeSPznByV9zCsE0Z24DLMq0jOM61xLuTKnRWF/vVrsgPMJcznvCSMWc9oLPubyknI+7JLTev7UHbgE8wvzYpPlXx7tIo7ljwda01+bvPxZqxH1kNG7C+S1kcqWIuRgdPQNr+z2+CajUeb9vd2e3Y7NmwYs+4GbAlvwpow12ROkjH+gqBaP84xDe0T945O+3sD2w3PFYHPgjIfnzzHQD7HfajV3CeYq3JXMlY/H7KScysOytyMGMOWp3vFXsj88q81hF8SgQMDReyNoNpX4x1BhfTroL3QmdSF0xo3HJG+8QKeExot20svODCQPr+tT6u8l/F2XvqBdp6NxdsZ9l/aWf0D7bRH4+2YG49tp7/5PfwD7f28M95eZGN/4/qbBXtN5r28J2jlR2N8SyLamcGz3WnVlUOE92HIO6kjJomrBNY087IJ/klYy2L8ZeqZ/s78nAD5Q/poESC/OFcfFeD7ZS4jdpfLmLTpZaUnQKeclHu/NqeKv1OMSZ5BojAsY+HTGs9B//WgZ9YtdVl1t2tzIEe8LFutWWWvosytyjS7rEmbE3arNuuZfxvyKBPtLc9XMSObwf9sXYZ4LePjwFv+vFHhEXH86LQ3JVzYhq/bLMonT2JeCCMnkOfLCRB32Z5ozgnMQttsV4Ne9yXwWH5z2CzytOcEWKdzo/U+anqp28jxYwxyrE9g/C5r/HbZ49ocYc2TuYNlWb02R+NvtN0cQ9t2//W5gR12+wdN7z/t/o846nhGBT6y6oT3m97NVh3hrNM8KvCuVWfz96Z3o/SHinVpUkfPCbyJd4x/Igw8EhY5+CY3MMbiL/k2bOz3gJEQnsAovO8pC6Gs0hMY4SwTozAHT2C4swzjFSFPYJCzDOMTnrxAkrMMcxeVeQE9GOdPXNOHHXFaxOtwq5D4+MZGRR+Fck4qbx/0oyCfKRe/EjJHXONomz7Qno0Hh9JETx5b2kL3bVR7aTxj7xHEOaxfAvOSYn0GiKLS7ZM/pPx3/bQ0JkIqB+eE2ZVR2kbga5NKmpQvRUP9quPU550GRW5la1UOV3l0K9Evcx81Mce8EEvzxhnBEpFevWhLXTafD13jbshLBY+vSRkrc+BfO3PjIdK9KzrhUJrk/TJu8MsNx86ReYNtu+4veH/Iikuwx1vfFbc3/7RB5fdlfMRBHfxe97Woe8cz5B2UJ2+M301udNt76fH3J25Ue+mPb3TupYt+99JL0S/vpT00JHHsO+h3V6/1jfO/yzcen//908Hfn9nQH/97RfG/NC1A3nbuRjV/tiVgVzZb+RoW9WOXfTtELG+GXRbNEbFPUI++U+Kb9sy0oPShniJim6FXfswz+dZZ7tBntm1250baWuo8txW3iXfL47bZ9nTolMt1qU9uT4c+eSd0UCmLc2zeldn46w2Kd6nct2/IOZVu7GOXjY7n4/37ButeXowxDHhOcNbluW1ZV8U/vmTVpf02bmOfmBlHvYYNjpiZnvV5pSE8XpP0t3NDfH1oz7RPwzqnijmpmqI7rtkFvfDyjR7as/GufTJ0adCfF8//t+HYHNPnWXjbPhn2DXBX4hHly3CpC09SOKA1hnNF7N8vQ2fKVWNh2ZwN6pm/z8DvDvpsXNA5FG1u154gbabKfK3tGCPzkyagX+4xl4G2ubfc8TeFZzatDe13Piq+uC/+/t+G4+PviXvj+Hv45R/WK/w/0M6gV+Pt7O23nWBDeJlar/l91os5kXPT1XoVSrxLa/zkZef8/qHmB/qx14trdTXgd84GFSvi9B29/7JaK8LWyfeeBK/gGdzaJCNWzj2eFEl/veC/a60WWHNrZZRrwD0euc9v+YkWW2vQnCSKDsD+ld8+xFy76tvV+G5RggiwXL+TuXUHyty6a1Euc/BDHm9OFes1cX+Ly+drYT239T1zJK+51RNlDsR3X7b2xUZa47Pa8si2PFFZZs1L9ot51cwrjHYAXvlZRnBLkij8C/pkvURrbiHUewplEzwidtJsI+hpFoGEUaIh1y2G5M8zgq4xInghbKqS5indfdsnjw1jXGu2CNCku2AtcH5GujjCuSm/XlnDMuAd/wd4ZiNHyDyIzNfeQR9fSllDVHc1rsW8Ok5jHncj6EtC+WDYv5Q1Rn6AdUNpAxoGYz35vu00JUfTwRM6zjRitJ0M7vf3GVuTHBvjUFyNbKMuWwSPoB/fuUL2U5ksmsjPfotx5U8k7ZC+9EbDMfYb+C5a05oHe2qVtFFUe8uzMH7w2PbpIriHYz9FnvEO+oaKmADueLjf5xktx778YhHk/NhnInHYEXvE90usd7vR5xZrX0CuvzUXrn/VKDH+wo3TgmswJ75LuB/vPKnAp5KPXscz1nTj0wuHTq9fmDT9fsgM7YSs8W8u/EvKlMeTx2qjho5nTPvqUUnjr3Gnjn0S/d8/1Aj4Uq+W+YN3JdZl94Ud7/BMmC2ChM+PVHzBOnHDlFgG6HLdeqkPLaVPJ8+Xz/iWxh2EK+jsbfyvSxExfkf4pTm+xXrFVju/rc8jH2/cjm/s+ol9+nqsn75et+DtA60+Z/2uS4r32XlU4duBo7Tv4jxq5svH51HT/xbnUc3rj2/7HCP/f6BN7t/2yP/1/fNPKf/R1uSXle1JezM0RMRu4T7gECVrn1hv25rH8t3Tf6D/hH/G+/ev/2H+nfMD7Xhfj7cz/7+0k/wD7XS8FW/n5vX/m315cP3x23vzo3h70/sd10sN1K0oV9rXK925yNLDfQPRzhQjSDmfKzKq3x0ovIwvpGyYbstei8ZID3cxl71134ZxpvB+iPf0kVam9M7vD95V1JeWeI+Hdr8RzHeLYa77RbAk3fh+dZKMq2sJLdYCi0Xz9/Z9V+3jReys9Wr/4uFE6CjvGfNz3SfcAXvYS//iogHH6oK/GARdkDanvX8+VSj58/S0oOYShfxt++fFJxiz5Z/ffxr0O+iA1NW5x7dGKB5KHz3rhY4qXVD66ccpXZB++rlaVPoV31zfN5Yr7i8vX6/0MuodRVJupzd+2STzUVhyW91BNB60/euZowNrFd1v135BmafkWdWtlRNnynvwhOxbW05Zl9oD0xlCTErwGA2JS0obktMvHKsPNYJ9Yc+7Ym6y5GKKJe8MreSjm1G2G3rkqW4R27Pb9eLoMUPGduiJjSf5RPDpP/7x+zLIn9KFb62aMUbsy+sub/UkaX7DTT+21iiaxTBfupjIuzrrRGLkwSLh/Y1I3FbP+1Ymin234HkseJjPEO8//dXCRw8CLiX7Np/vEknbaIuc6N5x3n/03Ct+5K49j/fe16KdTSIpgrXw1qJOSE8qWIP/l6C9kpFi3yUa413w/N29j/6fb0b3awM9g1+79dTuGSI54hnAPYXkbUIkD+TYLuieMfHJf3omzsC48L2XZW7g3cVfzZj49D/HyPIHdas8CeVfxMvfdlnlqSh/J16ebJcPRfmr8XKOS5ano/xZR/uMB84Sw/KWzpi4GmP585aT/JuEuoOJ828vFsFd0IXXgee2wxYeDdxVums684lUVPaDJ6QT4rxZk9DA2E3TTGwwa4aNfbhdxTvWZ4miXaMvatjtn9LQPtcI7h1x1dh7GdeT4Ksg/J39hkZr8zmWpXb/3WYh77ekbMkHPpY1Dwyw7slNyu7lt1Kei5MCf0TZLujrxJ2dwBt+3wa8+TNw5s100UT+tXnhG6t2OPAGtLltl4U3hoU3hNPYk4T3Qgfe7B2j8MYA3vwFeMN+zwPeuEXCNqf8yQH+LNBHXTEZ+FNH363EnwSJP6WoG9ITCp7E/yVs18KfMj4Df64D/lwH/PnbrSd31wHnFP4kAX+SfhB/LgL+/KUf/Lnoi3i5E38ueide7sSfi16Nlzvx56JnHe0fB38ID66HXAvjJLlGRU3Sp7tU+E4KXNqk1lNoDv0Kdc5qYrx3tJjv6MOuRBvcS2lzy7sml3qknnmyvHdFiJMDHtT/qfJFod3RgUI8GwnxNkc1yb116mrfQU8Klo9jbmqt+hfvmd6+cqPmVs/Gu6CHLGg6Pq+MvmTlErB4NvMn9YwrdFLPuLpQbwLGNdvRVlWr2autnVZbj1EHAk0xvyxpgDi/Tt79BVoALTEeWWT4WqosHKd+WCnE+l3LiM8JBRjjduphujUX6vOUeZzPSUON2NozjODOIaJpcdQs3DPwwm0NHOMAMfxmt7hKwzqXiOTqPM+D2SbgsniI8DJXyGqMeQeexTDhfXpo0oTVbut5qPDyvEst6q1OsspShHcPYHyLEFOF+77W/6S6r2B+pVPuOnG4Ju0ukZ4n+0ms9qUwB1rz+bzf13zk7780n9r0yw79pj+5TbNJaNrA1ddWbmSbRip9X9xH06rHQt4/dW0VyhOrSTdakionztvlguWpqpw4b5cb9KENVeXEebucPmEtXZUnO8qb8a2WZbWvOdpn+SirfZ73l+Wi2nBZtsypRrD0a5Pyeyn1YY17Es2jA9RfdInTYp0T17gmkJkbeQdMqbIh1rms94aUp56NP6bvDDiwE7S0St7r7G7kc5KM2/ZVzOQdXppWXXrI9O5AXdbLk3aPS/odWGfvUUtWc3x7wDtJT24xZ+9u0/uhuturokeeo07ebrOQ7ytfNr3vqj3dAvprLmZuHenf9VXwu1Px/37useL/+3Jv5tUeP+rcl6xzBJg74+bpQ+U5ktuwFhcofa0XLJYBVx6bXblxU4I4uxn4sSjBUPCrPDnQluZqoA034SW119cxQuaCkXqbGKfabUhSa8AzHZW8a+WTuzYu22iu2MJ+xEMVvEPO/aslLWWwteTdyyl5q/KE23/hQLGccuz5F5XOrmTY65auo/Sgp/t5F0qzxuc7OdABnXSINTYP826nSX/COm0h9RelG22lfjEb+hH6Fy4xgfOsH16X7QLvc95zJ5LyVvFeN3lXZ5qcY6926mZ7JrI+1uxR1uc8XL9S+13DMRfukdEGabHWUzQbk0KdZmFQrrP4jvyR441gToYrziNbX1RymXwEulqQc8gHbGdA12a8dt/1otzHWDby/H3bfhEIt4seHjXxJRXjzDZoH7eXGEG2O2Uo79qVtmsvPGc77Gs3dPMtkO27Bk7Z9jTpwS2GX9jDn5LAn5Zkl4gB1aemKv4UFoqPV+I5ITVpQtgdfyZ/CoNnhJNUmQH82IX5XWzxp/vAn2DX+wf04U+bUBc2wTH8aS/4UzL4U7PQBobBn0qEXu1BvQw3fbKuahdjHq+9ayP7Al/1ZiSp8jJ3vBz6qDcjVZUv0uPl3K/KQN+ENfmTXc47uTPSVXmyo1ywPEuVkz/1tI/fGaNUOflTSJaLavo2uV7c87ja4jPOtXwM8P+tdcffXSliOXGVa0dcrZR4NGBgrjagujRqynYWWDzj79KvLwp4lpX37TbgP9/vwf+L8P/P+E9bosNUdr1tO//iRRm3rvYNgf/TbX7gwHPYbhOxPsVp1r1d/3iht039Our3nQd5qQ9jLoHNlze0LtuHtt28ZxZ0kifGrBLyTkMhaQuyqZDzbYPtPhFzbhtyLM1Cdk4MybH/VY3d8nme92Kct/kGiSb6Mg/dDDnoSqt+N5X3zOk9vk3GxmEOw+3zcLEX1J4p4bYjRcwpTZUxRi0/BgyYG7kW77uVv7PX3DZzvpifWUM9Ogl/yQ3F29W9mfXM2cXYRvJC4EF1ilD06rCrttJf6gY9gsY+lT5RV8EGjD003AiI1KsnGYNE4Q2+abCpBo9tWyCCPFv8MOT+xETxfv4041FRnue/TpQGxGXGo9fpp0KmXRiI8Yy/ODWQ4/K1hO+5Jxq6pzIKuxo2U0qf8505jYwVoI3Q8ILa81mgi0jzycLL3FvO96tfUHs+OS869nzW9n9+krGO3PM5OGTQ2GkvqD2fsD5K5pg+k3C2YtAYozbeuvuS/LzwBSc/b3m675mspS8oXr5SyjYlO0b8NG/V8WC66KC5XvLW+pMDj+Fbu537XlD5Fz7OFU1dgLMxBHAeKYpkXejDv3PUncu6NYPHjlxoPErYnz5KeFmfdweE9ptF5lzjNcaSxmBLleinnGiv0W3gKSWjUq/owlpkYR1W0eZ6ynOmeZrv/Dj8sxrVOd6Mgkss+GcB/jyPeZ2Ef/x9qQX/V174H+B/wPQevH3Q2O/WqfOrxBPiC/GEOKIBZ9TdpBfi+1MDbRJHqoAjLtjlyQ01Low/2cLVG4jriu42A8+Zd6a0Hzxu5h2rS5TMLx3Ic6yUaacEijFekRiXZ7kWneWrPYgClv1nncpzwTOWzd+Y/bbduVULZCT4WlbyjrgaERQXG7E8nffs8hww76cfIeOOO9cpOK63zil3yr3L+Ptv1yk43uKEI9aoPzhWfWl6o9XpY/9kwbG/cY28mLmoFG7PW6f204nXxGdnvOW9647F7TD6bYUuyfIijKee52RfMnrOYPqS+4czdVJtiQgesmCyAs9qjpkyH93LDhh4Dpvej3pgoN7/1YLBqf8DDErbTO/+Geljf2bBQK6rOCWweR39rGrfrnGdipFW9HNKIAxaCDrer+n1/qRA+G4RfGFdnMZ+ZK8/c4rutM4W4Y94Szoj3kr8Be5ehTG4Lju2fOpx1ifPghXtUH5Tas8B41jqGOP8dYrOWUfSujjlRI7nq7DpZX9O+jmrZ/8v2LM/+n/r4v5Vng0OTWO+PlEgUsVVjOFOduyTdj3fz76bY59U7rutU3ofYxTyhTFpBmMU3FaMgt4Tc7DOZfvirBgFxnFTb5k52NKDm08JtOWqOx8v4xzdojCUa70D7U+Ra5PZCBotIp8ps8bXbtEjY+Jp/75vqruJe/b/nlf7fx2St2dKHkWajjwvc6i/UMm7Vu01rzw18CD6ccYwBPuBgd0O7ehPHWMQ3ab3/gRx1f3f3dtaeesNUfqH64+YhaFyLcD7H13oo8w4NdCBefrxXUcu47a1AOvuXQ+dxlR5wzm+rY52q4DjHNNKqUs0KV1ivCtQYOErz4NwPbnPxDXm+wOPGMG6TBVvwrHz7MZvn7d1oHfkPBiTb++jUuew9Y0cS9/g+v77edWHvacavl0wF3LLx89bOYMcOSVanrf2yofHy9593ornz4yXvfW82qety4YMyBTeJzDez0V0wkDIp9PXOXwd6XacN/NHYGzPK19HfZpo2r/VFUiHvFL5hBjzkdb4Pd4b4CcelzxnHYEd4mW+WmedvaqNl9Mc/YSOqHjgSujjdWViX/1QyAUX8xynb6tziX2n47n9et7Zo8bPNWqfKmLXPa/umu6YYcTaZzEHSkaB8s1kyb3iXdNE7HLUqU/AmPidlXPvwPOOOVK/X8xvsqU/Z441xwNbVf6IeH6LdLkHfcvz8fwRlbDZl/fkj1Dvq55XPPPz553y9zhyA/K3c27G2KHPK55p90la6cn5staZ8yVj7ADUXSt9ZfUt3/wVuAG4uGR+QyHlVsbzypdrw2oYnvcDPi/Bhuc9pDyrgLFv4/c1Zca+uY/6VhImzztgUuoWVk6BkbLNhRYN83wO76E7gHLyMH632vHdZs3+Tt1beqIFS/ZH2iCsoDPs++ponHfL8+EY036ZnzVTnutAnchbXSq30yS0wX1s0o8tM/ueUVj31950VZkdx3Xidurz6mzlFLP3/uS5z8d5sXCpfS7qJc+pGMOeNrrZvhadkG7FQyz/67F7XzbPfrifd/nWWvz1r8pusnjyUt2SQZVWHBjbz4eesLtPDjLnmAc9f/z9uaPh+P5c9V+Ps2+4TLVz+K+922GejNApav7jlD9sKffLwmuFjB9nzHv7CBFr+KvFt1HHhseV/fTlhN+zeO9si+2ssNoJH1F6nDjVCIIuCuspB6y96xQLtxb+VeWDh42/nfrS/b5TGRu9XeOdsaFTA3mesYG1mxYxj2nFSHzz+THwe6UHfq855h3S42v+sC510e2ieWzADVngcUWL5d1KkBuhrUL2V9acHjjynLmCcwujjP1d36TujB/SCwYqBuizv6rxX/bXHr1muxAFgdefU98Q7lo/39nr/ehfe85kx3wO/DydsbLuOHzbYQNPJ27xbHatr2KJgu3Z7bCJ9/OuYl1v3P1cb/ubZVKOPdd3r/vVhvB+5QO8468OO5l4VoL+k1RskO1be/+5Y31rTh2FNvO4vyr+8ZiM4YKdW1kg4wrO+at1py/zH8q71/CuviAwzipvdpaHCgInW+X1znLPaQGPVQ4YFTHu8MBzSof4RMrzzALqdjusslarjD6jz6yyf1ll1Jc/tMrelvpKhloz47TANVb5FicPAYzGOmAUOj2+RredKLyPJRDHMhrPe07hXOU40UQ8D502dILeI8vSGiVu1Z8WuBX1dGtfuqc8dFrgBqu81FnuGRf4uVVe5Sz3jQtca5XXOsubxwUqrPLVvdo5PXCZVb7ZWV55euAiqzzca5ynBwyrnDl34uM8PXCuPX5nuXFGoNAev7O8/ozAGfb4neXizMCp9vh7tXNmIN8ev7Pcd2ZglD3+XuM5M5Bpj99Z7jkrMNQev8s537MCKfb4neX1ZwXc9vid5aGzAkeftcbvLPecHYha5bW92j878L1VvrpX+2cHvrLKN/dq/+zALqs83Kv9cwIhq1zTnXA4J/CZVZ7nLA+dE/jAKi91lnvGB/5lj99ZXjk+8JY9fmd5/fjAFnv8vdofH3jVHn+v9gsDL9vj79V+YWCdPX63s/3CQKM9fme5KAo8aY/fWW4UBf5kj99Z7isKPG6P31keKgo8+iz33ihD0hrLPBMCci6o89CzKu8T9Yv/e9bJzxRPlDwA9Mn1lr9Bk4ft36DDqP0btHfQ/g16+76nzumBb+3foKuv7N+gpb09bZ4u11vxmzMC7T11zpDrrWTHmYF/99Q5U6636vfMwMc97Zwp11v1e1bg/Z5+z5Lrrdo8K7Ctp/5Zcr1V/bMDb/TUP1uut6p/dmBTT/2z5Xqr+ucEgj1jOEeut6pzTuClnjrj5XqrNscHnutpc7xcb1V/fOCpnvqFcr1V/cLA6p76hXK9FRyKAqt64KDWW42hKPBYT5tqvVWbEwKP4PcDyr5r/NWz6p6WM55VfLm+1VzP9adMO6Gf9e85XwD94blnHfpDomjqKIad57Zih9pFoGO0CHY8wxx60WLKS5erviLs81WsfVae3w9qkM/1z6p4I+7LjRb1FaObF2dznC7oF6SJA7DBYUMH2p6h3qAF5Dvu99ZPCFyNbztGo0/I4Wbo6YyBpm2laEkLfPiMpZ/gdyF9sCW931NneYd1UlSd09TeWOOOZ5x6iDoroNbHCI561qG/VE4ILH8mrr+838937J8y8b5nlN7WrCu5Z+hDJ3C8bMdtzbVNd8u57kxzNXBsf2Z7acx3LvfMpYx8EmVtI6A7oD7nw/qr+tSjzFyJsnflGqc3dqpxNa63xmB0Y43R99fPqHWI4P97Pf6ZjZDnyj9T9Oyx50cOwBarG947JnrZM06/xFvHxETLc/WjlQ3/1TPx/L62H2k3ymiPMX6d8WA8X8IzJbzv0Wm/1z6jbHr6ErhHTztek+dnTpP4QTwijnVBzyOeUY9JepYxnL4W+hp/9ozymX2oqdxpT7qYJy2zwPZzDlD34bTMJU7o8iyHn/uvm1zqXtd7kkUR7UC2xfW55Bl1Dse2v14jDJuEPN9Fn5NIpG4W9/9c9YzS840YbN2tWoD23Vvc4+zBKdAIc+fAfqzsVn4AD+9Y8+E/nmecJeaEAPeVuii65xn1jYsxO6I4wLXY18gyNb78PmPj3ibzh5Ae36E/0KJFwmjTM3EYZTPHtgWng4fM9a9b+mD4TKwP+zxTnv+RZ9tpu9FGcfrTimG7LbO+uRr1m/Cb+xrMG2nb7oeGDBmbiXeNUn8M9uDbH631Ja5VDhFN0v7hGW/8Jg6BWL7ztE6R8dkvgW7m3jQlRjybmaR8RXkyRkCsm+WCDVtZHPgMdpsPbfLZBblrvxe+iYF7rHI+lyWxfJL0S9yJcgN6qy9VFGapuMUW4uHnMr+cWEdfFHM0DIK9r89buLHTleTnXWIfuQb7n0gUgVet7zXxEPfAv8/SNT/viGVsB8eurWO8Zpaf+Wl5Rtb1AnM7ufynMq7iRf7W/f+f9r4GuqnrSvdKuhhhG2PCbwiFSwodJ8XGECCEmqAfyz+Jf1TbBCeEyEKWbQVZUiQ52NRNTH6dkh8Tybb8U8XJdFZtmnl1GzIlGWbiNJnW75VpPYEQQ1zGnZIZ3kree0zKZEyH+r69z498dW2RrjWdtd5bS2ctad99znf2OWefc/be90i6yoHreW/QZyTNR13A3v5nXcbxT3T64/gc7yO37jwG6+FNbBevsQ/YPu597ENfgj7oYQ3FjbntG2TMdwJeuCRs+okonBjROqJS2uUP1gj1URmuyTMR9I+tEVY+vgbbg/1ynOy5gbxjR5gOUf8zut11jPw+7gfUryjPJp47rvQn9PwSyxCH/ubIHOXYPp5FztVvnBs96/v5mP2iv7/BdTHvB+w/TVGHGrqGTsIa+gLPmWG9LfuPQvx/5H99f5XxcImGnk3S/qwg/dl/fPZvjPCZIgNa8S6+pyfBpq0A3MAzwrWlIA//XxQ/C8Xv45zLEL4pwLr7nUk4hr8Z/UK7nKwV4/y2ig+O07XO5Uig+3eWCztqnjFM9dxqfEt7nO7vnoq7jqJ+sK/keWPd9Hd5JwBzbUjufrVi61FsV4oI19ogD/+7pw368Lh2+af4m/O11xc94rpOf/+J48Lx4fx8bY6xBcjvRZd8+pvfA57szTfI3kRd/vj4jC7x/vd34AfwOaj0t0xUX4vjZNLvTqKe4/wA7FPU2cNs/JN1xiF8RvDj4FMklHUT/f2dcY2w7fHl9LdMk8tpnn2tsA3s0014Xvf5EPVNbTnCCQOe/w1Rv4L8soypO9l/m73cpBXeqsJrnXANz1EPpAoteK+2Nk14azvkP7Bw6k6HVnNUqxOOioA//PC6k+JBaWod+U4axNN6ocWgF97C/9B6AdrAszH8XtG7msztq0TDtV5YV0bw99v0+IyzZZ8KMIaBFPq9HS30+bWFwrY3U8l/DZLfqeM53reG6PdVUI5Gm7n9ZpBzHp+5oJCD3394JdXwiFqeSR8vr0sg36vpEFYbrhnmCSda+p754E1Y4+e/ePtzCNY77h/7+PMWx+XP+fkPfm/cTp4npyG+DX1tG/iTC2vw/F9L/mvu97AWDw/h+iseWqfXHBVaz/cRer3iDFJNuuaoQaf59LkMPOMUbl/7vOZfi3Tglx4zhCbJmeeq41GoP3Bd3jqin9q+7/jMuSh+LoGYlOP0P5VFoLHf6oONaKTfxyC/m8fvjKNfW/U7eftV8CevQNkT6W0V+Nn4U499O4Tr6rBWxP8m/gB/z4PPezk7RH/Lc+Sx1lDNw+tPSrq2CkOa0CKc2XoUn0HwGvqCg+umyOeBMK+oy3VpVJ9HrspVrytkO5nsT5bMG0LZfwOyP1liGVLKHtDPlr1OIdvIZBuuyGQ+1/0fuepx8l2TJcdxnLeCjFe0wiOnyTMKhaX4v2Bvwj606YRPayCOfjXD0GITNA8bYK6XtraeEXRLjy7H7ylCnfdXmQ9fg1jnyGKh6vcwd0uJbTK89RuILfAzin8Yot9dKoV5mnzPeNcR6OPaLIgtgDf8YuuOV34vPDIAbVzVaW7/nHw/AGOp3cf+cY1AbK1g2E2+/4nrFeesZ4jOWTehK47HPWcB5m7x0Oz9z/e+Z4ieDWGMdhrWtPQbctbZsXa1cC2Ftj0mkN9RC8fQ3sc+1xsin9ncrsMzKLY+zwxCO/OLhxyw1t+Ddf5TkGOGde6AdS7ohaPrWt/rIxTWK1IpXTi6dGTr0Spo69NpeYW8W3dXVyr9nTzaYi+0gb/JuKqwx1gGceYOwxA5r7sd8zGGxrJvsLFoSUyOz4zAfu8+hvrKHcJzSvwfGmEYn8n92k9pbP9j6DPOC/0+LdQZ2H1sA8Euvx0xiEXcIMMhhmAndx+7BfcSe85q+9DMXgKfVnUz/p8yzGX4mrytBWzBAKyXgX/7s+0xfdYIx14k53f4P16a25vxWf4psA+JfGEYnwVjmrybtGfMPNLL53wa+qE7GJwi90pm/NwFf++edaxtkNxHDuNc4BgQizKZLmibkkB08b9wLKDH2FgAfxnyGkl8uCqm638ZpPrEvadcTw9P0/+x/Y/BeBtRO82+n/k7eh+aNqQ6x949c46tPHsn93uD9HOHEe3UnTx+VX/2gP9l+k8rhGtbi/C+cOnxykF6hoy2ePLr9FlyOJ5v0/wfXYU9iN/t5vdD5YPK+8D3435fNIA6Oll4bXrRWmInNg6R7zCMCd8rJL9NzOJ8K+XXc76Z8hLnP6P8as7nUX4l51+n/FLO91M+k/PDlE/nfITyes7XUF7kfBvlBc6foPz1QcZXUX6K84OUv8r5Byl/hfMTlP+M81bKX+Z8CeUvcX6E8pOcD1J+gvM+yo9z/hLlz3K+g/JjnDdQ/jTnRyk/yvkxyr/P+VOUH+G8m/KnOB+m/EnOP0/5E5xvp/ww5/Mp/zrnGyg/yPnTlP8e59+n/ADnn6J8P+fHKR/h/GXKh4Gfnm+cEtiz8GCDdmRqjXf5BGGr8fqkHvMyVwuVhus2/Voh8yDeuxqvL9Yfk+Vtc+BHMe8KOUOwjQL+U4Yf5Xgwhlc4XhKkKY6XWm2ji4XMo5tbF43+kGFxP8Tja04y/O2Abwd82ubri9oT4ydn8Nf/KPxMf66z/lyf6c/ur+o+/MO33hn6g0449odvvTv4DvDszDOWDnn9B53+QIw/0BJ0Ircp0BLYVOt81OVwBvA66Gzc5PHWOsnbhtpNDl+T2xUIzomDMnzlbnLYHQ3OTS5PrbP5jk0B12GnIBSUV9xbsafMBtRssRUYS0pMRvO90B7I2BRoaOT94Lg9lRZb0Z5CS1WJieRvCjb6CGX4TXUwAH+TJ6eaJFKuzhP4eOoCmxz1fm+Tb1Ojs9Hrb8lptDez9vjV3DhHk9/v9AQTlXOY29XoCtpcHhvX4pfgmwL2emc83nJfQb6toris0JZvrDIqeXhZKqtY9ux8S3mBUm/5FtOeQuCD/iYn5jOV7CP5+yWLx37A7axNFbKzPU2N9uxGu28XaX9DU7z+y/aU2srK8y2VTE9Mzk7JYfd4vEHJ0WD31DslEAPrIiAdcgUbvE2QbXe7XZ56yQ9vNigI+r0tUp3LHwhyfUOLO6UNsYWXnc1W4i4Vn7srnoeuNu9CHuQ7OTrG5+6K5xkaeaJjBZ7wCjzhFXgymQp80NXohKHF+lfvdzprW2bKnc12R5C2SniKzc4OBGtdHtSzl10yfK0TWlDIJwqM8Tfef02bamHz2T0Op6Cel0bQvNch1dldML9SbZM/Ng0ujys4g3M+Cgu6rlZy+J32oMvr4TWyCvIlMnQJCmD71u6+LU5+gnq8Hxtq4/pjAy0QnixVa7HVYjMbrUZzcdX9DO9umik33V9lqbSVGqsZz5d88X3FleUVVC8+v9eB+8flqfMCX+psND4KPcDlvHOmXYkv9AI6qqBX8rk8EjFFTr+0geY0tAQk1CfwqUKsP6l0HDvJJbRUh0Nq8nj9tU5/bKC4awgukLOhKYfvGsYDrfW3MHlUIN9PFZbKPaVg0sorih8oL9vFi9XllVX55XuqqEJmQLNx9xgLCy35u7KEWxG0E99ulRB3G8M/ekfOlpzNuL5gXQC/ZfPOzdt2btnC+1tqb5G2bJa25G7ZzvoPmxIaK3F5mtAi2u1+R8P2rcLm7Tmbcygud9vmbVJWBWi1yB6UaEH2FtZgdvkdUnadO+jdZW8CFWfXkWXvd8HWsLtd9gCuRprpbLR7gi5HtssTdPp93oCLrKbsOi+svew6v73Rme3zkkJaodEebMh2+v0elBqEzZft9np92a7GePZRMExEjrXYLGXvdW/MLt9MabY9kO2BPQsdJ7wp0NJ4wOt2OSQyvwc93kMe4T4wMdCPnRJVg2BqcrmDwCHPskgqrySZEscZQU07FbzZ2+iDleffyfgCt70+sHOmvBA2WJE90MDLY+vWUlFRXrF/p1Tr9vqcfHftjDXN91VTwGlzBJvnqgfDmlWN7qe9xfm8/xUWa8n9PB8NvI2WqfzEXmJ0JVBokwcstg90h7vGBfad75yNUq2zzt7kDuLUwpS7vfWkODc11i46kXuLS0oq+T43VpmLoMFq5XquqrjfVlJcWlxF+rdZUPTbWg77v8yCHcxl+S6Pg9Bap0NhP4jcypLyqkpBWb/UeA8zH4wvLuM8eNHyinxLBbFNwFdaLPfaKi1VvD7hLWUxvcEOq+UUB3jI7wo6s+pAC1971O7eKO24Ld7+oeXNcczS64bAzg1ketQzxeu5PD5iOYn9sRFj61RghUBDU7AWFqztEG0vxvvVPAU43N6Ac2adSw4veGBPbcwFEw8BM8zHSXiwlQ41bwv4YMs443AOaltivCsAKPshEmPE5aMHUvAsMIjxAQwqnP4Yj0YWKtU7Y2EDl0PMuI0b4Ti8Qkisf267q1HB01BCWe60e5p8tkN2mEy/sp1Y04SvQ996aIa3Ow7G9Yu4CGW7Xl+LsjzgqvfY3TO8O+B0Hpw9rpn2nEHwwH5V+zbcgXHtKhdJXHtOe9y81Dk8QbeC97l88fiZqSX8o9QYqvQbtAcDrL43ft79EBz4g+jzfcztx/TE556uo4DDj+MAEF0HTY0+qBxoaoxfVwFnkGdTOQe8fiYXu67cD7PjC5t5D+xxOiQlkqbUXf/ZRA0rmDajVGUpsZSiAZOyzEV7yu6tvC3mJ/5EzQhlxNg2SVlWDFo2NN0GY3E3SfYArimwyq2ExeDIGQjE+GIpEPS6nYwj1+BS/N5GqdGZyuLO/2Ri/avyBsHmm/3eQCC70us46AxKVX57XZ3LQTvqaADLE5CyNuRsrtuw4U+pHyqq0mzEmx5jVRGVuxf8Clj1WE5VcakFIirBWl5SYrPcZyljFr7SatxbBpTkGysKud/hPA+UqiqMVhu5U6WJ3W4JxYXgSsBxVPld9fXgKevd3gOgCGej01/v9DhaJLZmK514r+R0HCQxjYSbyDnHOpfyGrx+12Gv525p38N2kFibk5OzH3D5sEXmEqDeP9I+ch+zn/cz30lCK3TMdNfF2fPYPpTy0JvfLeW5apvhHewEvB90ud2Bu5meWjwOiW5syVtXBz2eY39LeXW1DF9BTIHks/uDLtBHzCTMthO0khVMiVSQH2/X0L5IecSV2AAEl2DbbXa/Hy7RhpNLii+B+yEIPey16HMC3L5i5r77jBX7BasftUZ2a9DphukJ0gC9ssF7SDoAQV4tbIkgVA/aZ9k/aV92sDXb25rd2Jpd35pd15ptj+m3ktqX+HrM6OQVl0FHYdXhe0EBvJdYIGcf8cVMgpl69pgljtllKc9YUdFakQ/4vdD/ArBf4LQ94C/d8fZcyivIxylrJKqvBJMv8ZsWpR8gsFh7McQs/yHlgb5gPniUx3we0VzBjD8ifPGMv6oETyaByBm/xvpFBr5vb5GlzGzZzyYD8cQV8rvJOP/IekrTA06/Nxv9qDRHHEDymYJB13TdESccW3Azfpn1x1pQ3UrGC72K3dTtF4yOg9IBOwxPiF/XrBaGidAMrDMW3fJQQOGXQTb4HwQXlwDZB7eA+/k4Y50301BD4qEGC7BjM6uIT6R9EOS2QoC7n9SDEEbRw5m4ZkanZPxNGKq76lzgA8gcxYdDs+MkKY9pg1gAm4tss5kdR04l7qZyiTxiyKVYpDIrHpstL9Yvuvu8sKuZEtXxlSLeA0vkIVJgIhUdkfbFZmz2eN3OejtY3LgRK+NKYmmkfXx0+6l9pGdTiCP2HMwYGCzXYSfJIgdaODt1rvr4OFbaV1BiLKzk/TCjaZZcdVIdblRXQDrg8tj9LZLXLzXYA1KgwXnAji3Mio+hU1Ajfr1X2Zsls2R1N9W7PJIFgu6mIAvDZuJtOpg8cOjwTs6ScOK88FbnuRvtEsjnnYBAX2I2CfyAKwj94SdR6rg+TizaFGmf3V8fYF5IEPa4g357dp0dZsjJOwYOARhYzrjSSZMuZ0B93zBnf2c3UICS4ebWnw0agu7ALQnqJ3Z/EicGzL+9BXcaituviKtdMUOxKGNhelrqAv38lHmiTqsRNLfovhHWCsI3MYb8zrQ8ulwQhoG+DnmTQEe0+A800/JZoD6g14F2AM3UCcJZoFuBCi9My0Gghhen5WGgvpem5c+AdoSm5Y2iIFwNT8vvAx3uhPpII9Ny6zzI752WTwI9+91p+TLQyCsgL0UQpgamZR/QzNem5QjQ1j8HHNDIX0zLV4H6vj8tS/MFYezdadkNtPrstGzVQ4wyPi0PAs1Nl2X3AuDNsnwJ6JUyWW6HsGi4SpangGa2AZ8GOKD9QK8+LcuXgY61y7IhXRBORGR5DOhkVJZXLxSEB1+V5RNAh4GeBToFdAqo4TUoz4BxAjUAHQdaC3T4L2T5NOZ/X5bFRZAPNAto7hD0C6j1uCx/D2gE6CjQSaCfAc37oSxXZ0I9oK1Ax4EOAM0cluURoNVALwEdAKpfDOMCuhHojh/JshXo1NswHvzzl3eg/0DHgF4Bav0Z9OsmmMdRaBfoxC9kWVgC7ZyW5Vyg40CrgI79vSw3A237JeCAXgd6Gqg0JsvpS6Ef52Q5D+iVj2AcQGsuyPJJ/NLcBMhZBvhfg16BRi6BfoBaPwH9wHoa+xdZ3gFUuAz9BJoLtAFoDdA2oB1AI0BHgA4vp+s0k61XzeEKQWxeo7klfS3JWwmv689Oy/zcA/M2Yn77tJzH8tbDy4AvyLNihjHbmCF9V4zqTCFt2cVfn8mAHFYXvYcbcHpWF8++WuHVDHnkkANqRsWQzhTWlp65eDYDs7CdAXhFALNRg0YzwxDVh+bnd4mWznnhlOoPz5rOXDwHrWQYQvPDKZ3zusSo/kCGcObsh+cuwnxBlUl4PfXctGzQkDZyoymheaaw2KmrSoVmPoS6aSWxK3PsitRdDXXaYW9maeL616mpj+EKYlf3zNTFfldDnVbYt6thHwraKqx8/8UMYT9eFGYIFx/BCzNcFOAF9PmiBS+K4UII45ih/oOwv2tp21ZjxlibaI5+xxBuN3Q+a+h6xtD9tCG/50lD5ClDfug5g6n3CUPp+XHjGeMFy7mPzn540ZjR1iYaUTdQEQDKelAHakINkPcw1DCeHzfNrqSsAUDycBQhF+xSVgfYHzpnZD5MqHpzl9itqwEloCBUQz6/JPPcAPVeh3pTWlKvJpoeSjOGUzsXmPt0vaKlZ14kpbh7fpfe8dE57M3HF0xMnRk1oTTERdMtqpwufff8SErPvF6xTxdNP5hKaho/voBz8dE5E7sW6Dq4DO1uBDuZj+2bMwb05uhTGkvoSY32kdQzxovYYeMZM1Asg2wozU89Y0rDNb8ebOxWsKmTWNeSMaKL7gjdWRDe3rmta2v3Hdp9ikELeNNXBfhL3WCL6dyNpBVET2oKuk5oOt/U5If/ShP6iUZbffaM8dyHJmwYAJAD+VAMIMAaSSHp9wDIerBnWq5BWaaMEdEYLQoVmsIFnRatIRWm7AxdhvzqHrL6L5K9OQF128D2p7M1FE0NLbBAZxHnYnQ1FImwRn19YOM1M3PzICvHPqyH8lP9sJbp3A1rostDy0zhpZ1L8rtu6l6sPaBQwF7FdRbAa6Buf3RaHlPsP2OX1oxbUOsBLFkhAtHb84AtAp/04Co61vWm6KgY+rkY/pnY+Xeiuet9sfs9MfJTsedd0dI7Iva9I/b/raj7rSZ14sLH4+fJAiY6wD0/DrIefHtabr+JzFnbQlN0TBP6lcYS/qWm8+81vaOavp/D3Pf8d03kf2gKun+h6TqtMff/TKP9PHXCRFZS/oWPucBSurQmLLEsEAjCqCyoCfVBDAijckEOtFZ37qPx8xOFymJsoIVk71Fne0h2qTr7DyTbrMoWyA9LT4EvF06Dr9aRMQ5rTBnDR2CBdBlCnQZzOGzoDBksXS8buo8ZIh2GnpcMvS8a+l4w9D9v0L6i1Fls18NmGQFRS8H3D/xqWp64g+yVYdEUzu80F0YLQpbeu/t29edpH+o2dplMPbsjBu392MGCLlO3MWLo2e0mG88yMaOoYTFkweocQSVEC3SHddRQQ/ULH09cNCVG1moQVMrzdT4t8vkxviGeFzAGG4cxnNLK8tI76Z4Fo39f556CaHVob1dVd2Wkoueb/WVaT195r1U3oPv4QuGEYgUBPLQX8Rzaa+0r7y+LVuvu0lz4uBQ5WAoFSHV92gsf5+MV9VVWiJNq76LxDppRTXRV6GZz7019i039mUWRpT1L7ulcEV5p7l7WtVzbkfrhWeNH58xnLpLZwBnQFs6R9yzJssxkgdzQzeGVnSu6lncvQ6HYQH9mdFVgdm1dpgYycU1jl/Am/ir0sSZflsn6sWR06KJbQpsLwrmdm7pyurOber4e2ag9CBsgtpMBEtrMyyMbe74e3dKSChsizXZ+3Ipwy/j5ezD/AMk1w7sp7aHz47in8bMScPrDxRCTfB0D7Yzhr5mi/yyGPhHN4Uti529FS9c/id2/ESOTYs8/ir0Xxb5fi1pj/4SoKxVTJ4rit7buh7qJe+KyQByIopJmCwIx0JY2PGGCKx7HXIX+tAVleSWLRdD26CF+fR7y3p9H+jiwzhQNi6GQWBh+Wew8JnZ1iN0viZEXxZ4XxN7nxb6jYv93RO1TastD92UVyBIPy/I49RcdWlNGxxOwL18zhF41WMIDhs5XDF1RQ/d3DZF+Q08f+O5eQ1+PwdQP2+nZBBsT9fg6yG1vhdh0EdmXHemm8Iim8x2NOfpTTehd8DB/q+n+G03klKbnrzW9b2v63tL0n9Ron1Z38jHVvutIh8pU0pwSQLr222ohqLM8iPEnjkJsnELnFXTWJYY6YV7BuodEU9fLYvcxMT/SIfa8JPa+KPa9IPY/L2qfUcvCeAfvG04dg3hcS2z/WJvO2PVMbvfTuRDz5IaeyzX3PpFr6nw2N9yea+x5MjfyVK72ICx1WG4Y79CVAJUACQjA0coAAzBUBSFFF4ykQuEfB8f4D+NUmNOBkCwXKWJUK7pGFsMaoPzsTDmPL8t4DIuYWsBMfQkG75NWh2+MeR0wRTfA4MHaGGDcYfyjuhlfbsYoiURXRZ0LwqmmXrGOWAnjhYIzF6k9mRVSRdMfxzVywcKze8V6osCPzpE4cAfct010wRpXxAwmxJbF4mBjl/6R1HMFsbCYjMEH9Z6KJB4D3k+EATMIGKsibjF3pXTPK4uI5s75YT0E/sbxAjRP2HdraEFY3zkfARExmkrj1HGQcaoH7osUMkwIK1X0L6Ux9Zwlxp7D/mXC/eb3em88D1sBM3oDDN7rVAPmM8A8KBKML5oRWmgKp3emKdrvXtCVqq3DuDXNSN8j+trxQnJpjui/nQq2tBTekL+H0XJCulK7F+BM0P68D21NRG/c58uASX8lMQbXejpc5QJmhwJToljrG+Gq6JUbt2OFK/eXYIJ4z/4lmAhcnboBBvNPwdUkYEYWKHytCd1iITjX6tjSU3jL6Crtk4o1qf1lKugU97oebGrVkEzv15T3Nb457vWYvvLwLOEvwY8q+ljB4mb8QPtBPJOA8tYUUj6gja4PfdUcvrVznaV7bZeU3/OVyBpz3y29q039q7T76f0KBp+xG50BbeirCO+SutdG1vR8pXd13y39q6Lrtf+NB6lQJT/uvnMM2rz0hiyf1qjWXbli3afW47C/qVDEQ7iW8BuLmeAgfW+CTnX03kUTXRlaUdS5LLzc8uHZ/DP0fkUTWhFe3rksutLUvaRrqalnceQmU9+i3kxTf4b2Z6kT1EzQ3pmpOsjZgRtknz0py4Pxc4oqOxtTMNMvroF+PIt568brBM9rWgHzWTxmLxeF9yB4lmN9W+b3rNwWPMAx/MAB75kyF0MfAduqkLeXzamF7QXU8w7AZf21LK/XqNaL0r6IdtRzfvyb5Rzqohnqp5+S5SvzVOcS2qmYAO3j9Arxg4A//a4sT8Tb28OxMSh0h/oaB3zre7Lso36gTRPNDC0yhTM6FyoMdHdaV7q5Z0Ek1dirfzT1Apu0tNqZSxJLr4d7qIG/k+USrWpNFfXMj+gL0IyZ+ub1pjzQL7ZOWNXrMsMXWojgiL5nfjQDygpUBWjMsLA3pW9evwiQCYHGUf3QbvPPoV2lDUczb+nRMU9gIS59blfQo4umejH0hRsSBkij8S/IdY9CjJ6itBsYSpemcqCRROk9SyJLjX2Le2+CKIpGG3ikoHXHmHyO176gAJj5JfP/S8Ce/VJWn5k08HWMcWg7YDb+Spbb6PlEZlSr7cPVthRYPCPs+Ac5dhaHCfNPQf7gHPlnIX8E8jeq8j/DM8g58kU8a5wjfzW86T+Izyf+D/IHAtM0H8/8Mr+rjWoKLv6anfclUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIlUzIl0x+fZEgaRpE30MdYCwYzpZ8xvgEfNAJJw+rp5lOaqZKXzugAe/jDQsafGqA1b2a8lcm7RYiXs4rRGla+mvH8eRD/Ni3jY3WFLFoszGP5bUxACuN3iJTyB7mVs/6mMZ7/plPH6GWZCmRihTHW4FLGs+rCCl5+B6VfsP5kMj39O+MnmTxer+jm+HG0s4EuUPVnDaO8H9MylTe+MjZfXuU8XGH8GOvYNcYv0/zXrBcfm5eGDKq58VRKqxfo4nBTaZTPSqf0cnp8eTvjmxfG52cxOSuZ3AYmJ8LoKGt3itEiVj+ip7Sd1T/JqJ7Vu8z4QYbXZ6jaXcTqsX7t4ONj+JWMVjNcEevfKO8Xa3+Q5U8xvjk1vp0Gll+t0scOJmcHK4+o+pcojeQlaZL+v0f/f/aHPBG7MEwNaftfzm1Qi1h5zfDc5e0sfyBB+QjLH09Qrv8RzZd+NHf5DpZvTVDewPKbE5QPsvyTCcpHWb4+wfgnWflUgvrSj2l+7o/nLq9h+b4E5e0sP5KgfJjljyQoH2P5kwnKp1h+++sJ9P8G01+C8pWsvCFBeRYrz31j7vJqXj9BeRvLjyQoH2b5IwnKL7P8qQTlmSfY+joxd7mB5U/9YO5yKyufTFBew8p9CeS3s/xIgvJhlj+WoFz/Juv/mwn2J8tvSFA+wPJHEpRPsvzqBOO7wsoz/yrB/LN8a4JyH8vvSFB+kuVPJijP/AnNN/wkgXyW364q5/Zs0KaJi+trdLo57V0z49vC8fg2hlfbvxqGr1HJH2B4tT20cvn74/EjDK+2jwaGf/3JePwkw6vtZRbDN/TH4wVRN6f9XMnwpzvj8RLDq+3pMNPvlWfj8QaGV9tXbk9zX1bpn+HV9naK2ZfBB1T6Z3i1/b3M8CMvqfTP8Gp7PM7wky+o9M/wavs8yvCnn1Hpn+HV9vokw1tVeGGebk77PcDwA0+r9M/wanvO7XeNSj8Ghlfbd27PP3tcpX+GV9t7bt8z1fpneLX9r2a89JhK/wyv9gdFfH6fUumfy1fhdzD86P0q/TO82l9kcf2o5Aspujn9x0qu/0Mq/TO82p/oGb5N1R8Dw6v9C/cnG1X4Gi5fZW+5f7n0qEr/DK/2P2OMH/Wr9M/wan80wvB6l0r/DK/2T4MMP9Kg0j/Dq/1VB8P7VHhhvm5O/9XM8FkqvMTwan/WwPCT9Sr9M7zav3F/NqjC1zC82t8VMb5GhW9jeLX/y2X4dBV+gOHV/lBi+OEDKv0zvNo/6hm+QYWfZHi1v5w6zvajCi+w+221/7zM8IJdpX9+zqDCF5rNO6WswrI9t0l/1F8R6fmZF4gpNK7X3GHfHDsze56dlc2FyWVlZxk1fhX76LQfcNnqnPZgk99ps3tqbQdcwQDpswZPknICDYGgP2g/IOR4vEFnTr2nKYc8Uz7bVSsQrsEeaBByals8gZZGSoN+WsL/Y0PJ2KDM73TbEciufO6gkEP+QyMn6GyG9zpgoMxLnjyf42ywkb9MsjXU+mc4wNLi4IFAgFa3kWcm0+r8GjHYCkgjfbM3uhzQH2+QvNGmqRwiBv86Bv8Mb2aYOfZg0O860IR/YpdjrChV8n+ilMbO+vi5XeyC0fUqvKji8dzvC1n28mr8fJPTdG38eaVeHWeyPmhV55+cFqXPtKtT1OfnjrksX6s6T+WUn5/ypI42d7Czydj56Yp4mqKJ779KPYKFnXVynp93cupT6E0zx/irWJlWdd7KKT9vVeuPj/8hVt+kOt+NUf1M/RVz1G9g/UpRnX9zuvpL5t+hqq8+T/HNU8X9qvoeVf3YOT6jrQ+p7K2qflBVn5/Xc7ryS/p/mNXn+p9k9Ti9svzG/X9CVX+M2VdOw9obt9+hqt/wtiaOVi9V3Teq6vey+jom2MDOuQ3XNXGfayTq/6tMJq/PP9+wsvp6zY3rfx9eGYr1qa6vxutV9A14LVLU55+f1FzXzDledf13+PiF+M97Gr6kPk+n2drRqT4n8LH6fGJEVX0+rg9V7fumWf1pdv6iuXH/L6jq889zLsssbtHduP5vVfWt7D7SqqNydqTfeP7+J59/vh7Z5wTti2j9k1+yfv43az9XfT7C6ucIc9tfTv9d8VkTsXuZ7L6T1S/6kv27UEP67pt9wKCd039p5uDn+sRiPav/Fc2N6/9fBdlrbsgYAgA=' 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P4jvgnnf0mR34TzH3H8DLAgfgvOf8Q34/xHfAvOf8S34vxHfDvOf8R34PxHfCfOf8RvxfmP+C6c/4i7cP4jfjvOf8S/gvMf8d04/xHfg/Mf8a/i/Ed8L85/xBtx/iP+NZz/iN+hel43TER7ek4+UXp3SipL30oe87xa7ljv2bzJ/kSJucvCTBP3TS2fKHyMmy7Jc9Vrq9iFhlemprZznXyULbdzm/wTpeYuiclaQr9vFn3Rbjk8e3uye/Z2j0G7y6C936h/g3aHgb7D4PpGg/YxA/2owfWDBvEfNmi3GuhnDNpHDPQlg+utBuNPGujbDa63GfQ/YKA/ZKCfMbjeY9C/ZKBvMdB3GegPG+hnDfSrDfRtBtfnjPQN2p0G/gcMrmcG7XmD9oBB/3mDdrNB/NIG/Tca6I8YtE8Y6I8bXD9qVJ+N7k+j+TfQTxvdfwbtfQbtA0bjN/A/azC//Ub13aDdaVSfjOqD0fwb3T8G48sZ1ZdZ2hkrzZvZ4ZN8BVmXXOLpWvzNEF9b9OxMlpZ2iTWJma9JCs9I8HE51xBrETNZh+j9FJ6PRvXD6P40aO8zev4bxNds0O4wWl8ZrX+Mns8G7RMG+laj+m30/DDQtx+eff2aXbfJzuT/4sCTv3efPX/vinpWXVvII8Es6R6eX3V14lxZ577P17lCU+grOSXNWN9u8gh9xwz9HrtLOtyVuLS3K7Ggt+sBU+90X9V/dl9CX+5v5Mtyf+P3rribsUqhtQNriTYpvYL3U1u3mPU0TE3tWz+W8tn3nJXX6Z9emNou9E1Mqi+Mn/fDtY6o+yr25+H9SXyNX+TFrTD+L8vvB+NTx89NTL1/LrnkYFey5kcFf97i/kjiYzjQe25S9oGxmu4y2XeHmWXtyXMnDiU/fvXQdZ9Nt9e9PZVusEEcuPYprn2K3NOmNHysjP3N1cN89MkxELF+uox1PXRTbb2JOeoDTvFfRZgLcWvb6UiNT/U46kxshxLHwvtN36ZuMZaFTLpx46ZaL2Nz68R4niuMZ/lZD4+rjXWfs7PHzsl9Z9c52PFzrK+Hv/4PrbOw9YW+67jdqvGThxi7rK6JpR0m9so6h2tZ12J+LGzK2LvrhN073Aeud4rrneI6p4Rm7vAHh8V173Bbcf4CnIf4uQvioo7JJs8LFVOHcLwbzmnHW2LdPOa/O3T8E3W8zezO7jun53qm3pk/qvWSU2q9u4ietp/F+aL69xF9M9FfRPRxXE5f4P3Jvsu5UQb3/w1yfkpzWpJiTocWXlkn8vPCVM/65JJgl+P7vcLHieN8bnOmtEOa893k0MKr6o7y4yOXsq4jK7OpvymVxMe49eWB7KJyM7PsbWPj5VXZRdmS/oaqOcwSKmGWFlbeNTW1uT5p25b6pHRbavHtztSzrqauZ11bUy6Xj+dVaV3C1NMg+hd99z3Qa+9D/fWK/m6dvb+06U/rj1k89hdYsU8XH+vLrNhnjhn3GVKNsYL3uaU+acd91hb6dTnlPk3MY3fwPPsl39v4PfHKmeKcuUzdDlEfGNtYd39JD8836UZx3zucG7pO8DZuf8rMPOsdOvmd3F6TavsfWe9+Ptfi3MreL9yTe4Dz45Oc5YUv91/ocezmftSDDw6DfMR6c4hejtdNHqD6I5uPpY5s7k2Vm+dbyj3PLFLiFLjQ75BmaXfydptuu2Sx8nYHC/LY9doVH7rPqH3gk7gd+/sPfGxfHy/G9+iFbjmm2zekHp7293Ftf84r/mq3W88r/j6u6a/5vPC3l/vrm/b3rXG1v1Xn1f6K+dWfg02e2eLbdX72+N55fvb4rp/2N2ivBT9dxD++s8//g9zWyWtDcvvG1NOsu1B/rYVnaiXfAoVYd/H7ivHnCb7eykxnJdZw9m7Q4Ocn+flJE6upr+TXLd62LSWuHeV1jbk2dvGaz5/PUr1UVrtH3APiXnjngnwfiFycmFT755q4KiV8OrHy5AGXc2MqsbI2NYzqtcTnfhDXQI3nY99qdT0Uz211TTw4XRPF824S1ajxz1ETT3+umviN6Ro1SGriO6i/EdHfZ7P3N2n60/qbOuSxT5CaaEZ9TjLjPjOGNXHDjJrYy2uiqHtLTWLvsYu1w2Onca7dmBovwbn2Ol8HHCzkWrZE5NrYOvX6a5Nn+Ufy9XJ+HeT5NXVI2OdFfk3c2OUp6W4Qa4qpKY9dKvPtdumvp+T6x/NvPmg6RX3l5xK/t8+eVu5rua66oK6+fwruI6J7dKEvqVlfQe8Y0gtdKOaveGbcc6pYz4b4M8HCc9rhrOm6eUoce9avR/ku14tfaNaD09P1Qrv9jel68QvNevH0dL04aBc+f3qq6PNgoW4o/WvXz8nJ2evrO5Oz19eXJ4v1VfTfjvofnsT9a4/PYzB+h8H4JTT+s/8l972W1EtXfmNK5O2Jlcd4PUp1iVxLrPR19UN8xPPplZPF+VxbeD551iehXdhL/DxwHtWsUqVmyfVq7Bqxnr/lbrFWS9ZkujJT2+rFeryK308mzsVx4d2Kr9ltBVYbXMtqUwd/U/t/zP17eFTV1QCM7zO5TSLKAKNGRZkAwkw6YlDUmUwuZxLQJNh2UNDUepkUtOCr7xcq7XtizplLwDZRaieANlGkQcEGqr6xxr60gk0UbaDURkQbFWgiKDMJahDQmSTkfGvtfU7OmUmI2O/3xy/Pk2dmzmVf1l73vdbaSyZ02JYIt9okdn96fSI+EvJpLSFp9hL6XroVdSUDfHbA7+mkLc9CmvIMgH8GYrRelHrTEpJ0bNkESotW+zKg4wtSy5YI1+4RSVLZvQ2Al53yMQe2V05lw6e178l/g9+p9gba/lu1nfLb9Hct/DbAb/wuKn2f4ljfB+mn0SoYavg5aWVLAP+dDOeLvJwy3i0ye2exjO0YrSU4lpSyJcRice7lypZMUJ7HexM41g7IBuepBP3hfWV8zTDe95Sx74P+UT4I33sOeFfAkQH6t6of54B8s4KcB5lWv3UEH91BuBaBe5Gqy34qGul8uh04vnIDm5PJwOZ0lPJA4sXxWEOfRAMwJtQH1DVCHoLrpPIOwdUr8jr+oIehR9ZgOF+BR7+2frS/cmXuPPQTBRy7nty0BNbVYaC2r9XeBO/NIWwNuxAHz3TnEYPFKfcf85LpbQ6H4yYJn0M7R11rhO8LCv5egde+t028IAlgDziwgV63Uny0wPyaYBzXQ/ugkzkzYU0mAU6ZAKfA9s7HNnCMu4mydia2dppOwtYvAG0g7iXDO4h/86GNwBltfTeq7/PsfdMZPbw+rf2nsq72YYQXw58DwzXuqQpccf64FrUwxlXDDEYwTuofOAi/cY4Av3x1ji1D7BkYhwPG5NwxrMCNU+A2icGtQ72erFyfz66jHo3jbiKMjnAMPPRvpvOksMrHfsIwD4R5rfIbnyuB5zoVuFkUXKJzJ2zuDrhPAraKF3TrkAPXMrGvMySfGHEsxgoHXybVKnDCPuLer7VVPHCGzTugm3dAr1fRD8X/Y9P8H1Xfe11sk7nBDjlrsFN2D3bJFYPdcnAwLG+mvhGko2GZ5DXJxHs/lyWi7iNc9jDwtUaRyXeviwMlwdP/mmj+6EORb7sS6CkIuN2UR23g94r9V0VUnUEUvSTgxvVfCvavmUPdISssfHTYL8u+HNOJpeiDCcN4+mA8fTCevk6yVIQx9cGY+mBMfSivW9OWimezh7i+eHsceK77PPhE/pgBvN2tyHG+q0C8WQ66A3I8fxGO/A7k/WbXyO/BT/1C3xY/6kMLjmpywQrzWBQ94jdfusuPvhDzJ9V+hEdzQnsrFTmEsgD7J8RGx3UeqbvaSH0ym/gX+zT7EJ/hiOxqVK6Vy4n6flYYdSOEQSKsEuEUDyOva8OwDh+MGj7kzGb4oK4/rq+KA8L3dorCZZLmK5uxCfjsX8VkaA9xY7Piv4uD18ndALPn/Bce0eBVMgKvwxReXuShR1b7cQ7fPnad/qjgkiw3AZywauiMoIVUOFSYBmTgEwBT4PHrZ5KK9St72PPLFfmC/SL8zrFfBqvUePlOZhU5EBZVYH8gzISFuVIQ4DAfaGMYbCM+YKviSwpFCxekcslLggBTEXSNngHKOwg3WE4AzsUXS47ATxzLQa+uJO0A612icG2XKLgGxRDA9tVjbO05cg/w/hn5hCzNqw3YnIHAmy5m1/nCPJ8tHgebrIRkDaIfD593BKY7zV+tFs29h0VP9HUR4SwsdEpbP1Xp8H7xZliPU4B/5lsO+/n+QlH4+wz/KaBbt9Kn+i4hxfmBAOov94exTWzrLl07O+UA/+tj8TTXAmsAc+2FefbBuPpgLmGYbx/AoQ/m2gdzpTAOUJ+u14HrgHBnMLfZjZTPRgbpVOAZ/X2O/C6PyfNg9Oc6ekR7A66FUa4zWPgAL+uixxP0B5zrMqB7jZ6wk584Sj9Tn+MprAMAZxhDn/mrQumlE/dIuJ7Cwjyphfo2XfYdMMbWtHQ/+lERtlbqE8T2LE6ODLvQb0pIQeMiZYx8NE/MA/h6uv8KsJ7pR9/gq/9Wx9/mUPlMFfqiP17q3yFT24v6y5dT+ytXgctfBhGeevjiFMaC72469ybXbp39Qf2PaRl+xBHh1nLQhV2SgdzgnDlt+GF1Lm06/+aWiSVVR2fNr8IxIczRX3D5p6w9Bm8ugjiCuFkJeCIEZlBcQZ8CjD327ifaGh0/g2vkhufvj1I4vJlM4fDiYZ1NCf00KH4K9M8wOJY2bjuq9pkVYX0tBdovjmSf6AXeHHEZyWEXwrhrOMhjG1VHVTx2Svi8oDzPl2QDTm8HPhHgZ8qbQE0IYIiuE/cLEP50HeB9XJMnPlFt1V2uAIUlW49VwzVu1va//Ig7M6cdrk4/qtIqjndGfiXFHxuML+KfD++q63VqSMeD05m/tyWrCOggyZ6cFORH4pYGs6JGsiyM+uz5h1UYJtnbDAE3SW5ywFo7lidXROcqOLQ8OSvihd/og8lXeJ43GdfGal9rQHlstbcCjQD/q5uB8tCA+ywlzokk23oA7h9NTatam4Shv7yzX57t9JB2h6HHVgW2CeDzlStnwpqYKG00Od7xzBJTSZYpNTnLtJg0gI0725oJ7RVFbVXPJ9mkmTr8wWeFhVdK6vMz4fnjHF9kItmAfwskEyl1vlOitdcpN7iF7/1eNOe6JS8po7aSHdrmyE1O4rGKaF+bb9HuMT2d3duScA/tkyTlXm3CvS64l6zceyDh3k64l6Lc8yTca4J7qcq9eQn31sC9NOVeZsI9oGGwI9m9IRJ/72a4l67c6064lwP3MpR7uxPumTnUbdi95oR76C+aoNxbm3DvINw7X7lXmXCvDe5doNxbnHBvC9ybSGY7SYkVZBncK8uCeytq54GO5vtw6WKOLF2urb3Cbx0Ap2Gm9zL93uuoTM4a0V8S/Tl4H++p/nMvqYhrf3eCPlRB3HVZMLZ5Z7AP5g9tos+k20/JiDeIs92OfWcSdWFNnudcUeRIAtoygxxN7B/pUdWN0a4c0YtmPKPbP/SLw/LvXK1pG/10T/OMRrsv/4vRIr6Lv4XLqmDeUviSQ6pe+LCoyqC3/q3Ojcl6AXhIJZX1pUDHV0R4T57YbQi6o1zF4Bm5UNkLPeRCHm4hhVWOQI2rX941Qw8f81f5EsrsdHJ3JLu0RKpQ+pBl+Qbk25VUtmdE0L/bmvZTfxdXEW3hKhydnDs2c9oxIdsZ9l+l4z+dIIv+xFWE0SZMSw44Tnys8Bp455GP2Pc/ckGMtXTgtXeVef4JruFvTmkL1tWx5CD7Pgnggr+3/ku9F3R0k80OBMuJD9g1GE8EebKX2+xog3YI6Q0zv2MRXP9VGOewoEuFqU/8I4zxuoPa2GwfqXO4Amg/K5IJtIPzmHRQvd4ENrbXsYPrWQ806KhS+gVY9yFOWAwazqr69rnoqysPx+tGJrSfjqzxnw9tvjoCm4pw3cfqc2Cfcln1UxV9Ym7C+w6A/xvwPI4X9ey5/1L14ST7AcB3HLs6l1ffZ/egvaCfzFh5gCA9zHCuSrNJHLTVRSgu9Vlkvf0N8gZ1Mi4rduEhFfYoc3PtO7h2F+qxINfylyvyDdqO5cioC+X78f6fuM24Lk5PpyxSvUaxBbZ9qNMDhgPuIZCh5ktlP99ZKO6TA26mp4H9UJwkzZy2php0t8EnPlL1guWiCM8j3sP6xZJ1/gIiz1g5ldB7fdPfnlFVDu3g9wBZ6rhZ+Y7yVw+XZw5oaztTbxOlMXlsuZTZQ8Pys3nCZfeJ5eu2OuAu9SmdiGVFQc46Gg+p8wHchd8rPtBoxAIy2pjaM+glPS6S2j6I8prtIQYc0RTgHaDzfKjgnZykxRLc+y8VfyW6r/LzEZjlU7+yl7Q/BjJ6kjdlM9heAUd/SnDQAnPKATh3p/QMNn5JJB54nQd9pLMvlwpS99zuBf7XePXlEvLDSsCtxhsuh7UPuBoLL5cab4L/2+H/h5dLQ1TnAvvqX2qfxRHEQbRFsW1C/v0YtoftdMKz4fMPV8/5KlsiRttKsOfcOCfKH1OCjl37WRvwXp+yd1p3Fbyn4h9H7gYZkiF6Mn1AL0uF1rTDfryOugPaMnr6kZOusNa8u6f69dS9t8+cZqu63vMoPHsY5h90Z5dcLgm3ZkjZpXdJXTKmB/z7MZnseSiH1Izo93boNwPsQiuMEfQ9t34++Gw38D2hb6s/QG1JryOowBxg2wdr1Qfr1wdr2WdKHUtmIb34Heq8u1Mqou3vanMnmVeIDWBroG9T3xbany1wDf1VOOepCTEAo/a/LlbsTZAzm0G2NCn+zhIDk0MeQ/vgj2H8lQYuyn2g358pkDwcW5tt77Hr5kv9oizPqLsL4DIPeImn/6+iTK60gg7kRjy0AK/MMWyOVim0B9/Rfw/2zCYH2pfCjNVijiEYNWf/VSTcW08vek/lP885sJ2Z0A7cD2Of2M5cfTvQtjl7M8Durac/3K/xA9RHrMDfeJK9ksCYkgngFF1DixP4biwH/m0favwR4W0xBIGm7hexH0Ky63MM7tiCTsW/awB+FbWJzI6wUZ19Lanh4RngY9nB6fAb90Jx3YXLllE+hWP7VIEdwDEMsO0DuFKenqPTZ5mNgH02Od7fP/bzXpAVqr2K7f76fW2umYBv+ufVZ0f8x33PUxvEwiG/6nasPMuYNspn33/wXsj4F+5lIM9aJGdFI53aGKaC7tZylnitYfknecinAuuWOp54V+NpO0gAePwK0DNB31lYKKnyqf5f8fKpG+A8jTD7BOFUv1/DR4x/mUXA5oTrDWDbhYi7vl7hxfA9aOHKJXjf3UBtPN6JOgGudQDaYrpmaWO70l6APmOr+zfgykLoF9f6+8onzhHG2TdVZjEdn/9Tm7tFmfvMaUuFseZP93/+qY/ZCbp54s3rVOUTjP2QgvPYNvbza93zW+D5nTp5umzJUqESfh99dqmAPih8/gH92nGj6b1pCls/plsuE3FNcK+7BdYE19MN6/nhO1qfa+mci+v+qewzsf2ZGXWM59fwPAnkYRsBrslRw6/xdkA7f/6ntrbom7STwKjn+uG5+oTnugEP2gjywhnSWPEu+H4XvOfUje/mhPHl6caH+1+pSjzdcs7rqHg/vr8NcoDXw8ege/a6hGeXw7OcRmvBi6D9ZOTv8DzSK77DJbxzFHSRHN16DcuG/GF5er5xvS2CsjO6zkjxsIm4Yw03ErCXsmINt3NiVQJc0B/Mnsuq36XgNHwPHkjwP6ntW9bbgtBmBN8xrTc6lbbrse3LE9puhnmtHR4LZxi+VE5i+IJ2CdonqD/MClRKqn2i0rR1/VKHkVTUIw5xgEOv/kPrp5nSt09MtN9efi9BfzXU8H6VvkFHeVlb5zloB3XKITde/3Onus++jvJx80CP30sKG70ka/ODFel2wYB2LbOJEAaRdzR9CnVMHLMHxjtJN0aMb1PnUgn3Tu/T7p3ixh7/if3x42/j4sd/4h9jjz+mrMFGThu/frw4l+uUMX8m8vlrPrHkex4oq7iAlFbh+HH/3wuyUB1vE4x3gW68888yXvf+UfZC3HjdZxlvqTLe43HwZvwTx4pjeOQfmgzlM/PEeVTXyo8RLovqPkjPgB/BMe2aYKWENO7pniHt09EL9v0PBQ7LAEdxTvr4yJXvxs+nU46fz8p9Y8+nSmlznryOnzAc399d76g6h9eBYz+Xcavv/4Rk1QkwjjVnanh8v03jxUlq/KXlAo3/4nue0E8oH1P3lB2KfmkM1QSaOEs+8doq9peuAd1wTR7xrHEc+psGZ/b+9BjBf/herrTVwqltTA9ayeZBjDukPosR3bXJRUKfuJZd/Hr1nH4Wk2OiNLpUvEtZRxMppDG7U2nM7oq4Z5z/UG3psz9zofLM8nGeObFPzZU8+zP/UJ4Rxnlmm/KMkRQG0UdaTvxhPpwuWhRfvK1DhRmLGTIBnMpDnwwyuNe405X7JnqNeL0KHHEP9nMdvL0KnJfr7v9Dd3+5cp/9d7sq4bkXlfsCfK+E9p8Z+f0JrksfrA+Nbw7o2qzStRlQ2tyx+icBnHOmMudX/67iKdj0q6fXsxjp+Gfqdc+0KM+0JjzzoO6ZVngGeUon8JP397Dr+Lsbfr+l+x2F36/uGTeGNEF31OSJ5TyG/6rfC31Us4hXapY3D7TI7QNMH2kUd8g9A7h3bNqw1KHuGyONoBzqn0QcqvxBmbPy86zoO1yPP+ttTS/YyXQ10AvQl5Bub0mtcVtSVggY49Y20Wa3bFjjKDFjnFudgL/zzImxfJZRcW4tU/RxbkYRfdwCr8a52aSXSorhf6bk8dioTexQ9uRzAtMj6Ctk/Jp4LyZsf9G6AfcN9oRrQ0X1j+xR6Q75G6Pt2hCumWUkpjIQeqOXI5fOWRtiaxkKTW+sTakHufWUy0iczpJpG6uH5WcLCfnTVeayjX7h7wV+fsMuZR+9OxdEu8us4598f564mPqHh/ssKZHqfoDD1JQAbx3iJetxIkU/LpWixTdJTpdNssNc0sg9zjRyudO+mJfs8/HYpLIqAzFWRRdqz2FswSpik4zE5sz5QVlVzg+MVR6PlcIjBPz5PHJP3QhOhJ7NDYU+eYr9zrCvDRnWW+ieuuxi9nWG/YFktOvv+TXex9wEE3ncLbzypm/JbnWtiXdt6JPVtRcfqXb/XbtGyHNXAU1Fhct+IRrTHgdcKIhgXPx5ZAXK2CjobgkxhEXeDEV2NL6lyJyLI9Vo088p/YUI7yBe1dmpvXddsDWpxs1H08UAeb+3g/KZP12F8GxV/NFrQ28EMBbnODzXP+lxN/p7LORtwbNhq8OCcn5ShePlv2s0RX2ak4KOcsCJD3Vz84Se7WPtTQ+ir2Z+qsrbi4Lo55hA8Tzdbk7Ffi1OWVZjcPNjLavfcCkyIhIgpTEDrrNu/efujZefOUo+hNfE7Ku5b8XnF7TJNXw8vOLb69kzfns9u8dvLzWhvfpvaa/+W9rT4Aa2W7Iq+3AfO0BpAmUgysLFir2JNBqaXxqrJPcArqC8ybabv7KBjLflE8+2QZQVc7rLQN+/1B4wgN5M5U21q4k7XEi8h13JZKOL70oX7ckYm8nkFXunlL7zArxTPsb1U3DdO8b1vKQAv3yM62uS0G4pjGSf2ObHTxxjgGwbVL8TTvsecOuuF2nfnyre9vTIM7rrtcW67/O1742655/WfQ/pnm/Qt7lA147ue0j3vUH3nRRvWz/yfb72PaD73qAbD1lQGgkUl8bU3/yCUrqPlAf0Z4J7uI6OxP15oFeOLHUgzSIPMA0xui1R4kfXkiWwnmVO+KxXeY44WMOvHWT3z0P7UPHRXNihxd7MpPf/dJWaQ4b8WeVTL/6VPZcMOvDmt/X8aYYd+dMDBuaL0njGjPoDg+i/YzZsW6zGXRJj/YfO1LhRV0I8aE27w5+o31e8HU8vXty3UvZzMVaqoj2eXloS9ruWncF92LO3zyW0j/tiI/QI7XPf0v5UaL98nPY3vxXf/vGh+PY3t43f/oEh3IM+e/vuhPa3JLTv/pb210L7y8dpX8ffaPt3JrTf89ex2ge9UiaO0GTm93iH9PhVmwN0ol7QiXpBF+o9WywW6lyqTWLhfiZZuJWSapegXKkEebJipxprYHFuUObUxPH5uK8ny90OI+oT3lI88tq5v1T2Z5E2RxK1R70OWQ64TEQuJB7Zhb6OZ3aq+uIMO/rfOy9kfNVEZuRnTs4asEx2DxCPzYl+xpzJwQGwb5QYrgDIve5CtFWysuSl1+lkXIBsGswMfbI+76J6PoPKsKdcw7KhcFguKnxxUlYjwmhY/qRgWH6jwEI2Vr+gXJPlplwYX27HhjtcLZOyYsjTuzZkusIbvsnNfOKD3HQSA71mGPSaAvvudEWvOTBarzGCXmMklzrtt4FecyPoNQHQawLnrtd0gGzBPjIzlD52n013yvyPdad+I+vjqDqPnfF9zKS+rnucqeRipxX6sEIf59r2bmg7Cm2jbhwFvbglHX0h0/Oxn+gGm9N6c3xf47WVk87GiW0Zn1jj2DJZbYtIxiewLQu0lQFjS4O2yiQyhcK/Dp8xPWGrU3XnTKWd3ZNxvkSytvISrnn01jR4Nz1u7eyLoW1yG4Utg2k6hS8+O3q8xiocs4fPpv0c1M3dCuOtnaLN3foEmzvt9xxhGZ6kzd8B7W2cos0f/c4OFQa3ajC4c6IGA14HA2GK1lYJtNVyoTa2krOMDXUk9AMiXDxPGP9jfDNN0eBSDn2bdXAp/w/gYp6szWU5tHdAN5fl5zCXSpzLf0if8y7U5iJA37yub+E/mEvJhdpcaqE9i6692rO0h/SZQuYDbRIpBeaDNHqu/XWbtfE3QH9DurVoUPo7mlRWpfZ5NAlgcw7tOiYjz/irK1PRfzPIX6kPEvn+M/+QF8ryxht2DqAvy6zklEyvOX4B8nuzfcOEGn6CofC2tZzrNtSnPymc+zDw50Iag7oO87gD1AeHfB3GWvjrN1HuBByhJ5wu5OU0zhvuP9LBrnvWfZNLc+X/PsNfoTwrXCaw3/AMxjVgfIvw2hGf+032OzSpIkp/w/2CtMjtoUnuCMhdq3DZveJUE+hKFwSpbQR0l2tWciFAx8/FnAzhvVv8049FqvH5FybCeirPlk9kzxnpfjLvmv439owDrreOtEecWnvESdt70+if/nv27KkLtL6jF+jbI67pv2LPdMH1eSPtdTu09kAeY3u33iRN/6kMz06zboRn+8/HZ6fZjXR809TxOflQgZhzfsDNdxZgHj18XkNj5HF+wnt3+3neKRK83+Zk99us7D6MV3jzEj/vuFLsmADXPVeKLRMCvPC97SLTRWtqYJ3nNF2wzn0flwHXrrGTye0x4+SemGkyN2CdXDHgIaS/Prn7JMtx4XNlv9PK7Pqf9Ap/t/mxH9lvcQpFsyTZn21dRd4WhVvnSzXvvi28NKm9gd2Hdc79JbR/mb170uZoB8hxfK5rkpv6vTonbR6cRQS4z4O99kYuvmshjQ8Lrn4R96cL2pYuBr1HLOCXLv5faBNwME8onip1PfG2Q3juN74dk9qjfMgJen8bwDXoXvf3/SLfj7+7ld/DYhNHwH7LXLq//VKM96T5Usmg/2DOlPmNh3yYQ9XE3ZpPFrwXNS44GS1ecG0j6CB1/IJrn3IseGVgPvwGPaVuAXyCHhKxLLg2RhZvDxFyfcT8hk0yZTzqNoJNQhZEwjDGWusC4jQtSB/IBPtHyC2TihbsaWi8KeJfRcokxKead8uq3AtKG0Pz02MBaAP3kNEGRFt/2cVl1XM8e8Qdk3Dv/G0BY0e8pgrHva/pYkbg93Wtym+TGhtWjT4Mx66/qM9dZm9N8/tN1I79GmzkiXMcBvTv/6LXQmJVAfJkb8Mk9Bu3OZsmbR4QHvpYapuUNWh+YwrYnK1XNXGZoBNGc0OTOIxFeazVCPbO3x1+4bVhn/Dej/zU3uq4TEyCdTMDnk6gOV68KwO+F6RGaKxHP1fDv/Th3X60ofk2l7iBxpD2PIY5vOcBL+IUXjRpj7xw1SDmL4D99d58an898RfN/hK/lhdeAM8blOd7gB/MH8R8b4uz8QfPSY0/GJ3v5ziO+YBnv595HPMBz3bfYor2afmIkT9qYzEeZ7EXqh1o/ArnAuNW4pEP/Vl71grjNio8F+PA0E+9dgDnAs+/dtRH45d1zy+G59MVuODzsb/JC+8cwDaaqD8kqHt2FTw7QYEJPot+6pyBeHtm7o7R9TDkidr++txX4u0VjF3Of5VdU3Gm88w6Xqg+JQGd9gF/iAB/iAB/6EVdHHhEb1Tnz1l28YrqOSWnfIRcbF92fo27eZK7npCmXC9pd1L7cqS/pIiZxgd98RsVV7rOYFxQpLogVb59ThnIL4ttZTeNDYr4M0f8N1/8RiafPYTv4D7Blom2KvXZo9Q39MVjBamf3c6RV3P55ovFzDSUZan2WrgXArpFu+WlD0tH8HEV2LdAA32A/8DPcim/5MgdLr5zovjCYNCtzrttUkXc3HHeyUhzAK/zd2h2TrISo4nXy0PTB0/8X+K9/6H3TKFPBt4fde9hes8bKhr886h7Ar23PGQYfGbUPZHeqwzVDAZH7jmpPMc9MQHsM086wuEGewn9zLXz9NNhd9DPPKrT07wk+JwAPKL24g0Py9j2c4/4UD6v+JOCd/CbXgeZjOu/KPE62MBgb+Y6E6+/meS/MvHakdV+HOP5idcxPiZU4zr9qrrnw+djjhxnLKsgRlsF6ACxBpAhGFdTSfIiuJZzYhGfAN/xcy3JC6KPbj4X5MtJXp+X3Nm3nEztC03CuFKvY9nF/urGl1nbDXANaQmvz4k5JRM52Csp90Jx966X7h3zeq70/Zc1mkT+OyfmkOZEfyShb2lqSsBtIndG5kTL6O8J8HtO9A5JAB0OcX4oOeA+X6MJew7g6U/QD21sciRTuq52/aOF3b9Pd/3PyjV8lqNxiQHHVt1z6rV63TU15lZqUff23MFKCrNSaRl8F5TvKvx209zlQB7OkxjXeO9t0fCOXodrLJ7T69ixumb9goT7HL3vp/dbVn+y/krlvnAk4me4aZNaV/8khHDYl8Jq2wDNRIblnxSi/zz0ZLUL5Zzw8b1+kBm5BrInXNGa4E83BR24l1X3otb3jtVvBCyUNuE9eL817W3RNsZ7uOe1SPdeyxjvnXhl9Hu4N3bJi1psZV4qxoI951/wghqrJIhrjRiT5ghiLNoqI/OfqH7qcArmsdiqTP2l0rqFh/2mRWVSJ+gFBTQvM8PO9L421/7STf5lF6+u/v4f1XZ9Ypgwet0BbQzJr7vQX4J6k9D3Z5o/2PDkB7kOPAaTOJ/AfQ2Vv6NMpfG0r33qQ1pEHnf6f5X9ve5c8QFoD32Zez7GWlkMBjT//LL7RBwz4jXyrmYaTzPNjnWMPHSckYdk+Xcu5MWpRAonk12uMy8p4z3yO79duS7LsssI93qUewa49v5Lqp9JvgFz+tBWqNjOrrV3w+fkrF7LZHdvzuRgL8rbnSB3CVd4H9ojnGKPVJ4EvQFgZyRlzpzbwO6/zQZ2v03a0q/4U4Hn852ooxAn8UQcTNbUXY3jaiabQDdJk6gs6HCJPGG6CT6vPndQkRsG1M88pSN6jYPqNXtF9d0OWZMjbbTu2G3Bjkk9YdOCusGuSVykn5T9PHNBJIp6dDf8Rt+2EXTFnAXpsZcmcXWoI+I8ihakN2q6Yd3g0dPyQpSdZpChb/2BwSZ8vlwNvDoyZ8BG42cfgDb37bPk/2OfreKikuuk4bBtCebdvPThDdrcvtbGZ6G+5lQ7yObg8Sis+61LpBW6tqkcPPkvKgv1/WxEWfzQm5Iax3Lh7xXecp8l/6f3WSue5JOkyuEVYuVFRgnXAMdgoDWzAjzmn2McG84F3s+dB9+RpnKeXOp4UWnnH4fj1xzjNnjPbHHxySC1lW4+ib+vFDG/JywzOwa/z8PrYPsIf7f6zSeBj+DvTqwts99/9KuAu/Mr1KmY/uRu0emUnwMcDK5fvID7RoBXiFOAZ7nE4C3MPKHpbRjzvfJ1eeGBfrzG7MvmE2wfyhIq6t14AvUwaP+V3VSfO/S/Wh+Bz8fGT/I5tjUN23JavmJtlYSKIuav1D66HUeVPvjQJ+GuE+p14mpSrjtChr4N2nXnMuV6TsgQKR+5zrssynVrqKjPDNcvH6HBpeGVL6ljZXGCOzYsdVz+vOZLLomAHQ5wFuE91P1n4ifAvOQE1TNdZnrd6g9TeuNdrf1sXZfDulqHcQwsvhnheK9C2y1g09d+qem0L76kwavpONZg+cj/AGvPmUz78bo2fI22AercsD7K3t6LOh+x6i9GH/GdX2Ib+/3J/dq6l+r6qD2u6di4tk/slBdGv9B0abwWhGtHv9DGmK573/w5m6MR5nhiC7ueyKtMYTpuR/0LGu+2D1L+kkvjk7YqcaiTKmAc3YXpf9B0gN0c5kN85kcezCu61ooX4+UQ2g7N0H/987r9Jio7n83Dd9qe3Erfy1mwJ3zVGO92wLtLnh89doTh4mMAD8UX1fTEGkcD0XxRTaovKkXni0o5N1/UboL5zTV5iA/N0C7C9eUXtHlvVO4jzHco9+t1963UF1xYh+teAmuQpqzNgy9oa9NA+Qpro0Np4/u6Nkyfsz7QXuM3sPtX6e73H0f5yvINjh5H2+OM/+Bx6qvKPUDtvkDuvuNaPNkEZQyRP2hj2NIrL/zlJE3fOv/3+nhM0Ie4gLsG7r+vXMdn9yjfjUAzqUqbT+janHecyTP0xzH8t+SuQlpBXg38G3k18mzkr10xzEV9zn9awTH8Xvp7TTdZ9U0N3xRFetJoc8/zal8/F4/3aXg/STeGcK9in8P12HYdj4Pr5yvXe3TXrX00fzh3Yx+zl5FGQ30MNkaAizo+FS7HhzF/rrvw6LAupm7y6Piits/i8+308XkYd6Tm2OFYMe5Iqz3wO7FSbo9hjBHGFE2KaXl2pU2JeXaiaCL+sCU1uP6qUfd8Yibcu1C5TpKT7KdSKkIYN3sqPYj7sa7WtNV+b3LQsfI5bY5T0eeX7A7SveCArWJWMuh7JRnineehPmjJJ6lZMZWO1b1ujAkwLbDR+IDujBoavxoAPa8L6PfCzfqYfC0eVvqdutZ+MZoR5L0pFY49yjVihH4wNgz6Qn91R0oW1UmbMmrcgRR3BPXS/Yts0rpBoOVUzJ/GejVtjq6UzZQ3pnBe+J4Vi/1e63sWcUgFTbYlFm6uVOC1LdlxAdN3A6E34P4se+cFmCucj7qAlZ8U5J/t/3015gq/3r/99iTyKagFv3IIrrCItWYWU53ySvs86iu90o78pPF6iyjM+BWsxyzn7RlZ/TVGYmr8gUWU5WMOE/AZ/TWOzLbrr6GOWtNvrHo+KV3C+yaS7rSQbY4cEnHw8FzjjQGpcU6T1FBARHzn9p+sPYHv3X7/iycWGSz9NV5iqlkO/3CtTSZFGDeWaypbgjVNLzZsPlFDXpx08X9x/fjMWkOS6RhJp3NoTSuRll1srJrDfybyjnTRlB6AefU6iONyjJvlzUWpUjIJB/Ae2Eq84IqIBtARCK2VGgQ+VxLkPcq9W0ul199lOp2FZFc1Z9qq+FR3zATrY0qtCF/1vD5nZ460Ow1haHEuT+2JVaZyA8gvhNSsgUCqe6A2tWIglBocaEjdPNCU2j7QnNoz0JLKDe5IzRpsS3UPdsPaOlLb1+P6daRWDGJ8UZ7xtdvPFr/z7tax661iPhPyg0W/i/cvcWSji3RNFVl9AouziQsUMJwvojjemrbDT7wbfoK6xCySKe3f3OADuyZX6Ptff0HAuMQSNEn4STiSLzxX7xMWzpOiKVzsGtB/ZqZy9cnw2Z/CYeycMyeVi1nhmiwTpxE+ny7OZvEWKUoMEe0TPz9xWRZk0/5bzqvhoylgM5TcILakKrlkoH8B/viNqVlB2d+W18Q15cny217i3eoV3rwQbKnSXOFNk19YXwJjtcTFm31QbZVk2ZT7QZVN0YmNzta0bGm/rUzK9vwKbCs5bL7lJolwZRGPpUwinlRxAvrub71RorUUAOeauLaC1rRr/f0pwdXE+8FPgOe59r/8no/FPxVGzH/EvcTSCOGAT5Ski8nkDVrfl+4xdtvEVoK29T2Rkfkn1/DqfCuTMV+qIKjWQ1lGKtaz+PSs+p9v1HhXgxzkU8nrfYnxEO8+F7/+lUr92n7gfSh33t2UWL/228e7GHR7SyryJd75dXKPI5lcEexPrnDgGJEH9SdnwfreRHnTcLL75WgyV38qOevlIfhvf1ob84GUgHs4OWsz0M1K43namqtw2JGkwaFkQg3/NTx7CTzbCrywO+1x/hTwRsxzPZDGahQGkC+nuunzy67/cdWQEX319z88x4PxY9lVfFe2uMoUcFtTGU+1ptfw3onr3NOBRknq5nBOajDc/oxKq5IYmhBw3wx2dy606QEaRJ1W6NvhtyJtA5zNl1b7+bBLdJgCfE5qVsQK7XjCWCepTow9rcG1Sw66MWdxwbMjuZdBlF/JID+Q954Hnx3n17jnpZUtmYA5+hNr3JcozwrVZyQvCbpQ7qdQ/fq6ejPmAMBYc6C/RY3suQfOe5zafk2cpXDXU+zaB32TgVadSxEfP4hk+j2hTH9r2kX+/XuuH/HX4no/Xcxy6LawepAR896zr38SwFYE/EeczCAaTqKvEHGyp1GXz6HgZFz9583x+BhIwEf3xtH4qI5vmczklrW4tJoUldK8fw/YUuYyqxRyp6/f4C5dX+uORAPuyED2orDI8Anu7y2RsjusUrN5Nq13EeCOOeY4y/wvJFvE7D1WoPkBl4XI1RijidewNg3W5w4syHA28xZqJ7/otkinkCfOzw5SPpTG8FV9J6C8g/W51VrZWKcb/TAAl5iaT+duOku9cdxbxfrXjfHzBxkRARnRC/KhF+QD+vQdICN6QUb0gozoBRnRCzKiF2REH8iIPpARfSAX+vpTtbwJ0KkiY+ZO6OKUtHhNsI1064V8CWvENhSX1RFPxgguoC+sibPl01qHXpuTL3nZXw72U6e8iUd81ePoi08qunMaw1ELuaP6kgZ9fK0Kw9JxYYg4y/0uIR9xOB5+wYaEeFTQVU8pOtSEr1EfbXIlg62K43jit0p+RAKMzxW+nC6n5txgbHF2gq7XCTIc436ZXi2Kd3I1PFyLZEJfqjzjS66ntTsI6EvhpCbXMqp3WQr3cN7Cpl86l/rfrF7K6us+V23u3egvVeCC7WPeALZXecF2P+na6DffsgtkIMknHc/4sF0T1V+e4Jt+eXlFm/wMr/ZJuBvyQbbGWsH2QH1H1YdOAdws38B4U7mILJc6zUVl0rqFZRLqoagTTzjN7AcvfFY8k1AvPYXVZyPov1R4GT8oL0Qd2QjPh5Jpnqe96VSQzzNuvx11gda0MqnbYKxad6tN4nmbuOYUrpvNSky8kwDvFeFZtGHRN1NIbFnXl5RKxAT3YSzeUwEe6xbi98Wn5IUolx7coLdjwG6QUU9HvyzIqic/yEW/at2Tuho8qQG+PMUdzAQYWlOwxk6G3VyENjPdYwcdr4zq4JlU1qjrlS22DWvr1TqsrRfY/AXamnlzyW9fzS0HXD7XPrDtO6Htygu2+XGtzWW7/KTjcqqHAD4DPuxaijqbA+wzxId8ZQ1w7ivX6/LuYJ6bn9DmGZAx/6RSRLra9nT8ur0AOhjWLqD7kKuTfNueVOXiz5Q8X4eE1wFf6l9UaA6+By2cQ8JcfPM6t0/4wxYf01V+9lTdeo0uzydLHSz2f0adBfpKV2rl8cmbeIwNDsvyQlVGrwHamJ66uY9TbTuQEdKTWvwjH0X5HOwjqT1hdjRi28hzwpFH/Cuf0OVmG0GewHN4He/rny99QvOpQd/1bP/IZjcbAu6SM6rcKQO5k0Hf8cCao14YcmeD3ClbH3D3DtS6s2PZ7r+JKk6Y/5gmZbfcBHLnxiqMaQ5wbzvmzC1hcuflmyT08VvIXSB3ihS5s12RO2FHs4OX8J0Xnbwid0qCGAvvJe5Yc5KmK5nLvvHxC5i+ZMH69alZ63ecQv52iNaBMKVuZmsP/G7BUyN7IhHVVhQ+vs8vPPSWJBxBmZ8fU+WPCv/ur2uovoS2YbOyFgze7WEah033CJsc6U+qPksNfm3DLLb2P5Unmac0edJCfeJttMYHUcZ+YaMuflWxZR0nUB5An6ptDJ/iV+jXZra7F2TNsos/eHj7H/dQHejlhni8t0d18gTP/1gXL08mAG+UEt6ZqdSgRBt/XpoNdLh0u3mwhjfN9jpebtT7/4oiU0+Onsf3lfaORtG3FK8vTUro6+ApJZ6ZMH1p0vr48e08xWgnCdbLerrGra6X8Qzy6PSHGM6jTzbqwPFWuU6LoQW9YTXP0Zxr8uE+S1E0rfr5pIiIa0XXxRtxDMuv5oYW7A3jGjZxs/F5pzm3VzRfY/KFFhwLm3ONUifYQ/0pPQFzkQlspg9yTU1WaSaMx/zHMmkCSbPK8t8c86wzl3gsdaKp1CZ1EtTN1wjEEOQLUmcvYXH4aXSPbSHmuU5HvCyL/JuzWYs+tFWtguegvXrEc6HYLKlw3X2C+b6of0VZs3uXrBA2DtS4dw7o6+NZnEYK33PEw9pt/tqTGh5avxm9fr9WcD9wivnEqd38JevTC2NbdvFDD2MNp+1PPUpxLv/JsXVAuqZAT7t+kxjzscJvGpIXpijvJSk0hu9j3V3kwzYFD16IYY6uRHn6+08kyOIkHU8H3Hk/pPL0apWnU754SIEf8HJ/NMpyI8wfVfjRL8v4uauR/HaN49Vfx/P0fVGVp9ddnY79kU1uVhOb8XR1fQ6FtPVpgHd2AN4jznj4VliHNCvigcd6TJxJgm5TU60PfZQm21bQR7Y6ClK3Libkkaux7YlwPYP8/ntG8gyfAbZAQeqVCv48crWFYC2Y39OawddbbWDj25zhJNvl1+fZJPhU8Ko3bN5ukxCvLiDbvod4tYF7xq3iFOJXywCzLfF7f0p7CP0Y6P9DXwbFk8V7QoiL+DwPa+5Q7OL7yGawiw8HkmndaeI00LxyXLMFMfjEPREH1vL7b+J+eTlpxzZiy0hPywOEe/mZtZqMruUC7o0natzwHNjJZStDJ3C/tiBSgr4lisd5IzhUAro24lFnStARe1xXf2XEjmI+S6wtblF8lvwJNffl2+jh0asZPdjECSc2uTHP2wh8JfNUfDwT1rfdpehbR3GPKDVI5TLmOEzX5TR8+Jgmw8FGiFaeYvEt1FcZsC2xBHPo5zJoYyHqfro1mRoL8p7wbAlj7/gcGE8s4O4H3aOJK8tX/Uxos8G1erI4m/IK9f2NnzPfe0yhscyvcYztrN6WIs/ydfSXGQvwBykt3xlEe93Uz+x1Yz/W38ugucLCkSf8qNsiPO6E8SLf/7NCj93wbjScvwRl8euptiXm3pf815ds9C8HnE8CPBHeTPd7wLawprrrN36T6FdX6j/8s8hh0PnTu9OWCon169B/Tv3pgUoJfeiC3BNDf3pA5gZq5ayBkOweaJArBtCv3iQHB9S6z5jz2z0MtpbcPqDm+ybWiUb/PNaGVn3xu2pHdKV87HMNwfOoAo456SuoT/6ZWr1cRh+eBXR6jDPJti+7OFaNvH1OR7bUmlYg0TpYrcwWMiu58bVKHMZa4FeYI6P63L2EcxFvWQVHMgv3L5L9rB5ne6GJNLiENy+ltVpxHwj5hXkggjWdXS2r38jlF9xD8R5r0xQEygC3PPRT9SuA3sSP1IYNfZIbn79YGOcD4cM2rPfr9pAbIgES7x8BHkN1gLHeaQC5tUypvyh8XE1zBlG/S3yuWQ7yzeZt1cwu/iSCdluAszkDxFgxp6RQshbnVBWkZC8x10z0WVJsVXPSS9AOygcK6K115/TWkrKK7PRsyfzoDb5VhnVog+RjPiqMteKC6KKqOUbgd0AbxhttVahzYq5+dunVPmZ//5Xpn/MLKfwrOVXPnB45oNTHwftkvj/X2sD8Ilc1Mr8Ijn+sea/h0Ef7FODdXwZU/6AXYEfIbUGMc5nTYZOWEd8rD8D/cnJ3vZcU1D/zKxV/bhjx/XhhLPeRAuorxJwTHAeOAfl6/Bh45826ehLY1/a9pT7V/9L+eLxM3CHr9L31xb72unjZ20DreGFd76ww0p3e3gcaiwB99QJ99QJ99QJ99QJt9epzxtAHkJg3hv6ARF8BrSVFsB4rl8/qGxRFcC/aS6ygx35TsH3v/T7q/0gYv1f1f2Cs6tNLfcFfxY8fzyo4G6zYmRhex0z57M/g3JOVfDXMoaf5GyffpjWsTKADELIi/KIirxaDjsLX3iBupOfKWfKFx+b4kDdszyj1eSq/8XH03JQblPrx3QWeyv/xJfqrs36dMD/ck8OYqKfv81G9BdZo16Oq3nKv2AlznI++1QW/q0XdpOcxbf6L8d2n/9uHtMFX3iCKqEu9dsJ3fEjDD9Tbu2kdUUt+LYw1G+jj6AJblbnsaingtoHtPUfcORR0CwvnSq1D1M+Rz5GHcrVns6tQnptv+aHkybRJ5qds0F92pEMea49Uqf+0h9UDnmdm9YBVHov7lrgfSvdCKf9+RlTPukC+ra876lyt2ltX2LFuBO7PDoF+waeqNPtJxLTghxHjgqsj/IJ/PtYBdmMm/EY/ShvYQg7OHSPwuwWu5+Bz8NsBn5XwWbTgh3WLOXejGz6XwOd8+LwNPhfAZzdxN7ZeFOTh/Qj6YND/wpFsa2uaTdpwOfplyuBaWRb6cGqhLfMtpZIJPk30ee3ee6XZcD0rxvRDsNfg+1WvYLyPJf+NsATybVehLO9ybTHsquZL8inOEENToYXiUD7dd7OQpkKs8XcU5o37sB209nS2PXARhUGczoGyHXG9YrVWQ5SjuZUF9uUTcf2ZbtrJtQ/0c+7B1rQjfqxHGSU9YNv/MzfEtceaOG6gmcsaaOHcAzu4ioE2LjjQwW0e6OJ6Bro5bjDMZQ2CHTN46BGtzinGDKdCP3uCik4NMKb5pqSibznp6evHOtpFP3SG4TNQ/EMnKboatJmrYwRgFiq+OtZCsiIB+FT3N9QzNFntiSIq11qn1vBDhFtNSOYcEwm5W0g7tYXXXljDw1pHll1/bRVJvtaKMCPJ3lyVp6u8NWCr4W89wufvtpB8UvxlYOvTxop/foO1jjKq3ghHqieCDJrssUl8UUYF2mb7F4H8Kp7oBNyJYA3pLsLF6JlUIM/MZS6J57hYDltbsCNLq3j4ToqvDuIzyzl8lp3bgPeWw73Q/KudO4h7sINs7hVOHgS7+99+lOMCvjcSU9SGn64Ax+KIMLYJ/nM70S8Mz3nhvxz+LfDv4bLq+2n9uG1XcWSSHWM9sXY47heEJgbdTxVPrPNED4vm/Z/5CG8ckVcDsCZ0X5VkrROufVe0clxjCdcTBb0xN0f13/9yhL9cJVy2Suwy1fIP1sbzrN0XIP5dExFe+8xHaxBijdSPl/pVeO8EfgNjxvkOdBpCvJk87sbxZgKN8B6bGJ0c5AGng2ydanLxnaOTgZetTvdhDgjdyxz8wi88t84nLHSAHXMLrCWr4Vw7q4bnu+eI3aTnMfT5CB+v9GONHnX8VrKR93Q/J2Ie8YVBVY+bm4v8Eu00vvs5en4DH3CI8zKD7h0wrkUluVKHCWwIkOfmssPSTlOABxhFhkCvkOV0J++xisxnGXQbSKkT6dyt0Lme5gmZrPi55tpDxcYBch7SLK6TxWUBWhNWZ/qE9T+GOe6X1t2aLgEsJKRpT61T2l+6V0Qese6xt0Uj4NCapFq+6tp3lLN92pwDQEudpH0A5v0o6n9dpGLADnNGeYGy0RbQ5MIL1Jf+ai5HinP5yuvEKNCFee/7Pr72enHfBbT+/wht3JwBsAjliZ7uP4qtMuh9IZ/PvH/9iD6x8pfxa98Eeorw3C+1dR884j9/jdY3yivMjROwbufJ/X7zpZv8VHbDOB/xq3H2T/nw2TthHTzdm6C/DSP9cQn94V5xYn/PrI7vb2My4D/Mk/YFbWO/JjwLNbTJBzDrBVj1Yh9mjpRg7WrVTn9fZO0MkYoQ+hWE9T/wCR//DGuI9jlMITfaLsJD/5boun38335hYY4EvCrSRpjP2nomyAfcEyN8wCpOPRPgPQGjhLiy9vKgG/36RrzGb/NhTJznt1sdwh+e9/FK/bVLlHkOk57eZKB/kLEuzJ+icc94vsJrR3xP+LR5dlwRcC/qWgrwdFL8Rb6Jtj18xpB/blTqS9AY0Kf/a2TeFC77HwPdKsDztTPFnRcF3PH6/3V264wa0Pc/DhPu+VpCUuweoEXC9fSx+xqu4F5UY/HV9HsHrf91W0RvS9fOvzpOPzaXTZHwfA+UbR7PtRJf4gDaeC3cxG3Nwz0aTxvw3JJrxZ0o+xa/FZD911kRRixnr82BtCNcu1vkm4Eu6bnKIOeu3SPahW2CsHCmZElKqQZbyYU0PHPa8wLfliOar/mnSKxY/+a+vC0TtwpN5O28Od/7jUg8M2LE88uBBnPAbd7u9PO1TjFnOtI5o78dBGxGoD+kQ6TBNUO1biOXFala+DfRmgb4VTJLFIAehaEAjzEulQq8yeIrg0Spn8ID30O+sg/r0qE80MGC5ggDLZtBfqHMQtmCvJAH+2EZyM8VCg2FhhPPy7kN8CsbbGDUB2xV5eTHEfT1GkhvL+rL79Yk0Kes87UBDi0S4/XlwKjzeK6PW7M7R/VfSHlamPKxdGo/jTW3TJqfavIbE9pPHHOiPjwpYfw7E8ZfX53gK4Q+tgzr/Z3XRxCvdg4HeaRLilMAV5p/emup1KLQ6sZhjCEFOizZK6JMRXrkR2ohtjvralR6BJy77H/EFupPL/K2kIow1c8f2i2l6MZiTAd63HHEZ770HQnpsZPCpxD1mViObnxIfyotCkfW+UOAPyZuM/2+FnAIcdfK4ZnW3bnC+rsA99OzuklWnXm/URKKJ4N8wHHkRzpIMMxHd/rpuSPAA1WabLm8hi8hz/C2h9Wx/d/VtI5rCqtVnUk2AR4DXEqukMzrjJQel1+KcVDf5GIdXH6HC2B1S+5GWkf6j34YSx/amJ6oz2/+yzuS+S9Ov3l/tT9sYDKc77CJBw1o886x95+HsimQS2PWR+rf5IkvXKHK93Q7nwLyBWCwBem9+b/9olHXzjdwreQS6uPmeZeIesjy8+LrZxs5tn/aBbwH4YJwYjC55qwwWfNNDZ8nP8NfWKWt10Za4+sbGOsRF84Z6zjh+XA4NtTFVl0cdIfPe5zHedmBjnH+zP9iycX549jo+YugixAuow7PM9+dwfQgtd8J32j8sTId78XTFl+SQ/emPQHG9x6gZ4/eEkG/HllcFpT9c6zCQ3slxv94J44N8w4Y7yNOxGe7kF4lLJwNvM/4MEdMuYz3ZVQh30EbjViNoKfsBd5nrGoiZflzir8E3jcLeN/9g1bQcRZzWXUyuWEl6JERGs8HPA/r2aI8WXaxrSoZ7Kej54Hs5DBONMPeBmts4RgNmWkcl4W+gzYN6qFIp1T//7lai9EdufUIAV3bkg/2fXjr0zbQtY2ga1urMO7hjXBZFV9kq5jMl0n7nTbJ0FNWhXXtciiOgk01Jds6Ffgn6oothKM+JMRZ+B17AGgO7LW6QNEPewnzTVKax+fwmS2TEXcuxphVHsdvgGcC5hq3F+wZ1Nd3EKy/b3GWcxzNOVZ1652n9Pxkjn0fUfSJYbTjy1ZOGEY8n2RPHq5xI5ySQAcEvZ7CpAnGyivfN8B3sCOZngpjqFRwd98Z0IVgTRmPsNlbp2EcPoNb/SoVbhzArTtvt4UHuLWH8dmtT5cB7I55LyA3Aex4gJ0RYFdWMdlhlPbPLQPYGaswVsHjKZUqlTF4z8TXG0b6PEj35K6JMH++LUjYuOhY1sLYUG4eALrrYuMbxdu9542WW+WTmdx6WVL2xoGXeULDfuTP5v2FIE/BVklKf5juJVnTnVj7HnES/Q4WEslrIjbAzX+KO+gae5zEkwY4mo62Eh2XJS3gprp00Q9jzI/HOxF/MF6mofiHjep+pwnsPAOJ9I34v6rH2XvC/JufJ8gT9ImffNMf+Zkif7l2gBPXC3ZwL9jBNB4JbOFesIV7wRbuBfu5F+zhXrCH+8Ae7gNbug/PYQC7uA/P2FD9Z+g7Gx0rE187SeW3iFvIc9cOIJ4BXz7yO39gQMkf4x4HHdlPeRHfdR3lkUOU/wL9RYdF4Q+v+ag8A9vDvP/Hkjl3rwRDoGdObrggnj+VXKjxp+VJY/OngI4/raL1dcfGG4zXQbzZMOHseIMxZIl4czyd4U2Vsk7eUfrIZOjPCP0Zgxy5zsoF2hyKDeSwJKXpeF5YoDyvaCLwvGOg7zUDzzsG+p4xf44LdEDPlYBPHbHypADYeO0x80eynyNOF9L9vn7Q9R+b5QP7tw5kSU1BqnEJ8vNVoOeh3FpFVvtq3l0qUN+BAc+LXEllhIlosstyIkjXhW92iYu5gLqnlrs8QX8qSK27jSjnN6oy8U7QnXfIbF1xTXfLQX4EhihHwG5UeceWiTXuoQyNd/RnaLxjSeX/N57bifpSSTbwDrY2GzICI3XiELfQL4G4hfNqUs4/9XTLorr3i78XCaPPM2zSnWfY9jXA9OtN/BDMHWuL4/mlW+CzURl709fx8NLyKVz2+YMosyfZjw6PxIPk4rhQJuOZq2jroF6F+hXYrZL5JJPnDd8E3fq1WvUl8nGvS23jhW+09S/hesKIA0NnHnXzjhki2mBh0MkRJ9CeRLwQXhvwoc9mcQrDD7qe39S4kyc+zvOZTH9YLuPeFc0Ny102pJcn52YjrRliNpKYcP48zqcW6NCarM1nyxeoN6De5XV1f/0ozydp8RToJ9hB3CP88OVfxPNDK61Lc6Nfb09/f5Xe5yOK+2SwfZJq3diO+ROwqU++4+//AmCm0IED14ziZ3qE4W0kgPwmDLTCbAX0U2YMUFuBpAf1PigKT7CnHxjCnBMj2AbX4L4X2AbpfdT//4tx+PebSf7g/5PAv6EtC4XZucFZ/JrBGWtX4FqyNQY9FeaD57+hL8+DudPnafD2ZgZ5vnmGeHwiow8VH1Tei343hIsIPHvx5/G+rvmfB6nNgn4EwF2aA43yEWXeiIz8FvmYKBvD0QCPcSUIa7gW64rKCx1Mn7OWT0QfdTatDaX3U6OPGv3Y5RFYf8ypLL5M2gJ6j5HLiCA/RX9Fy/kBnu+yivbTbJ5MX2J6UgPLocolp7FmU7bT3GuTMH5x/6Jt/lURzHljeX9oV6FN5fy5WpOym/o2WtMy/bROBMamoX8D1vLVB7W1tOP5qt2rqX/D3ot7ztpzv34wbq+fP/TQ+DwH84TDEcZztpCedch3bA8oMSwgb9R1vbMPcCF6WESdz7z/Pv+8k8zvTOcJfMJM9cKAC+kAaQBpIdzHzjlmMgljjb4OZ5COqbwjR2xNQnk5C+P6KV4m2s2MVkbTgzeWSAsRatuf/lnC2VmxeNv45w/E00JmjOUJIl/o+OpRHvOSUQ/mQB/1no/5TExnv/kUu55MeX2GHe3XqacYDfFt2eLNUdXXcMuI3a7yk4qEMVmi8WPq+a+E+PYo4tjzYYpjVptongg41nSlKH4R4DFW4SnUR/R7zMS2cuqEGnfi9YJU2xJa++90DZWVKPsVeXlVG9gFORmP0nwe0C1cjCYtzvtIj4PVYzAEWbx1UbA17V4/kwWzYwbF/v9vkvUywL0e5Gj9MlLxygPwH1uhq4lBgnzinoIlgvu1LLfDM6mG/2/le/dksHc5pu+gjDVF75RSwc4ybd7gQ/7SSTb4eMV+Ql8/H9bgvvHUaLgjHnxeGQ/zVafiYf7g/fEwLz8V4pedUnm0Te+/GdDwcLS+VkJYXQit/wzKkx+sHJ8nf75iNE9upTYH+mbA5kWeG4j4UA9U90eFhTeg7zLC77CJ/acV38yOPaLeL3O6Ut1nynKizd9CKqLD1F+C3zeH0f63chXhB3X9HwfbtYX69GdQ3yj6EM2X2qgfZR/GmVKYRAZaSM+AALzMEzgm8jmzxflgb2C+HM/niJ2ng8yXyzvE3TA2oThTmqf4+zxtOdTPL6zO8OHZV5qsZvI3nFFKY2Gxzg/WBfIm417rXF9YJkXI65OxznOGjfL77BIrtZPEY+pa7QmT4v8NoA82yqmyVO93+2eA5KTq1izVjrIlpw/X7W2hnLwGsGqPGsindN1e/e/xbaHrlo/2rR3tVcdSGhnhV8Cjlo0p20uDepmrxF65Mbab8TL3iFy3/ff4OLTtp6NxaPGXLN8Z9VDLp6Db4T5FBHQ7sMM8EcX/CnYT+m1RxgkLs6Wpse+O9zePgfcj+x8Pjj/uE/eNHnf/V/JCA1kRlkLywpIjTCfNTIrXSSeYgAYUPULl2ZjXj/LjKK3X/CeQK7+cylsBBw3oK98q8pYrxTZDgN8ycbeA3+0pQb4oulXwtIVE3jqT0dX3tsBzs0RTSoD3WN4G3HaIpgi+j99zxOQI4PO1nWIibMbCra7w2Hh11wMJ52WH4/Hq0L3xMAmFNX3YyIWZLHCAHpsOssAxR/R+FeTLaZ2FbHquLyEXRTJI71SkxQ0GhRYdVjFE535TlSfQJdJzWZNx/kCzOUq9wWs7RNTxpibjvkuZxHuA93yO7+N3h5j8Oeaylktjy+XRuHzgeCIuM7l8138l5BIcj+fHh5bFz3/tcb09cLEd+X0X6HU4LkLCATEN/UpcBPeOFn+O/ps0+82fMx8Wym7+c7SDOpxCcYbUhs9VWsU1EwJu6+chrNPjUHUv1a+NvPPP/6XxTuSDOxTe2UG/bw63AO/sIBXhucu03N1V56Gt7I4s8pQCX3LHqAwry6Z8lPFOd4TZoXvhXntsA8wL9eIDyZpejLow4jSOBfVjag9Re3GmXTTU8Msuflt4gMZqtzmmog2no4HuiCYztnyu+PMDY/vz13x+dn/+rvvj547+fHXu6rzRp3/dUm3urWkoN2DuOyI+dc4HVL8+Pbs1m/r2J1AanW3fweFcyqo2Kmd5qvYy6o2rvsD58U7HGSbbcW09bWVS1HOT9IvhY6LDAXb4tjJpXXGZ5OCY75LOD9YXaUDNkeE914mrjAE334dnvnGRJBJ2LMfnAfftfXCdvjtbtPQF3eZblkjF0SVV7N2mXIGOuTeMuP6L4V6xYf7EAdxbE3JvkjzQ/5aJZVWkOZvGmXSS9yk/yKFxBu4B1PkFJo+iqh2APlPVX4r6C8Y1rPm3YhPA2oVhzlsmpgJt7qDylJxG2jwm8NbZCl/6PaXZMOg4HodRaoiyd48f0/h1ctqjoNvhuMuo7xlrw50rD48qZ1Mg/1V1wCGQ78KtJdKqT+ATZNuEQYwlz/QRkOVna6cjbcRve1XL6Vq36ncxGjW/y6G7lX3sx1w+wLEI+l9Cpx91Mx9Md14l1x7e+vQxL/PBhAX0v0wk3Xnof+GLjnnRB9NJesKqH8ZTcpPE54DeDbqGJ4fmfeWbc23Srx4tq0Dcx/nknA663wjbqibzNml6t6vKAnOzcBlUNovHatzG2cYqK7fX0S+HHeZrjJKh55jAkWNgH31aacXzKbkyao9irISR3BjBXOGpXwV4E3nbwfOzRMcxjFeJCEj/6hnoJpJKcZO9kx5B2zB8At/Z4zAe44tARkSwJgI+g3zOiM/DMx2Yl4h1efr+6Ec8Rh9ny6dMXmfddzbbre5qmkfXs8k9s6dGsd2yqO32oALvo93yQtTVkceA7u1M1O2ZXo97+5GoqtujPq/q9qjXZ92tq/dyMjiit4dOMlx7qvj/eXrNyXi+tOw4y/OpBZyfh+eBKrEtSCczD4Xcx4EOAkBvuFew8Sttv+ToZwE32uVbJr76MO5h45mvwsLrJNUOi/OLAo0s4bLYPjul4eusLLcI7fltPoxDwxg00HOYXQGf7y1S8+ksNFYJZYOH7xVr6ViIc/+im8D2KLtc4Z/udQszpDUk5EaewfhNmoQ8tIP0RAXXZ3G6d9W92n4o7o8Kl/1M3MHkSFhYv4Duh56+S+Ofyalgv4dKgXey/dAWym97wojHqJfR/VSmV8YERb9kvKlUYryp2Sfckk3PNcKamqTZpvCmC6m8Zu+kx9T9p1rAp/eXjo9LB09ucptO1YzyPV5+J3tvJ6yzF3joopBRyuS4GG9AOdwTLsf1Axghz56AcHOFxXWuMkmV0Vs+DYzI5i2f1rhV2HNkr6Mo+rZgvmavhDJ6OdVD9opC8QXSndEQ/8CnGu4gTYQ/CrlbDiEd30fPy1p7GOl4qWDlngc6Xu0wZy8VDT1rgI7XwPweU+j47TDmBDCafCvMN80Sc/6NNAlrl3mlWHIY6bhuhI7BlgAavdKp0XFKhG+yikOH8Z2UePqG60fp9W2ODrBXhujYwtS3t4PymGMwtmYY299gbMdgbG/D2N6Gse1WxmakfqSRfvg54ppwkI3NcaW4ivKYPeOPDd7x0HcSxgbXHfQ6G5sV5Mb7FeOvvzm6yc1Hx1j/O9h7p77R1kOvm9/8Yby9z38YchsP4l59cADliBXW0VMZv9dlhmuIH8suTq1CXh44EqR6nHBE0+O6ztTwOUrMnypn9bJ1XhfGKZ+bvEM5lhdjdgurW1mk2C73Ux39z95x7JaPl/qdd4y2W9q+eNQdxtxoDvN1OxTd4W9Md7h1gSRcAzwi55iI+yzEM1uhz+1xugOtBUVpdVsU5xb6hPFOjH/UYh/bnKhHsBhGFueIsYxd/wq5mz5i+tSO1T9Z3ZpWTfPJPr8nIcblCzaXJmUunyfMJfCF5lOZp/iyxoLREwntGqPxMLrwR/Hthr/BPEumA3x4m7r3kqXsvfDK3kuZsvdSouzZ2tieLcjt/U7cs0V/QLaE690C7U26Z3wcXnxqk7t2DB72o9uV8yVPMZsRz2OMngzxxh78bbOrcgHhkEHSL0dbiNBcBSvWOeNxrx/1bLSfmb7kju07ru79OcS24xjn5JBWJcTrqDJyKujBzd0ht8rfROClC+4efy67Y5vc4djoufxageWWGNPPxrbPRtOAfuym44m0EHQoax1+H2ihvw99PWV0DyBZRjvSWoXfQzLqqWWgt2bS2D1mZ5TQvPxVMvJvm9Q1rK17z2L9nhvu1xO6X89iinGvPq0K44nZnpuxYjLq+nONyp6bla57cjfLo8TY9PJ/azxI1Tk6D4TcDf86e3w9/1QRwDTJzvbKgjdjjD3mNmFek1pzLDG/SZixiZ4Hqsbac7pY+3/cOlbtMV/41VHX/WImXBcGB/2No+5JogXuBZXrmG/bmhb2Mz76Rh87Y9QqNXMV0UqQteayw/4S4AGmBXdHjAsKIvyC4V5+wd2PNXAYx3833ctAfauFxvHfHQGZHMuBz04ax393xGrAOP676y40YBz/3XVmA8bx3113kQHj+O+uG+LcjbVmsJvGiOOvvTA+jp83sDh+0OFigTHi+AMwjnBSjfvB1Ri/jzS9QsDz2jCXZIsB6Aj0KweNB8cYfks+fsf8ARbLz2wsvCaT0oeiHIvlb2A2pT1nQg3cGzuH8IlbtRzCHQC3o+YadzOXFVRxsdLQHhMMPbGAgRuoNWQNhAzuARHabzBUDDQZggPNhs0DLYb2gTYDN9hhyBrMMQTXC9zm9ZffosbqbwqvTSKTvNCnl2ymvCwE42gC/boF8LPxBk6qJMSBe1ZhLhgNEK+zDfptTOMAjwMO5G2N93BS402chDywsZCT0P5B/td4OyehDYQ8sHEaJ6EdhHywcTYnkaLDUcoPbWVSwH04qvJEkIORQPEVMVJ0hTPTkBULAZ4E3FeArITP4iucao4AxthXUhlls6PP1oP4RNQax0VBPpoh7qRxZJdjvqUPdYhyDusnzLYfzKjhCwJzb7MEc3z4yfa7vbkdXM+AkiPnakPZxOQ0O8cPxtKNv0OfuISn/8fXhXH4cM0I/w74Nxkw71XLPzVdWMOXwPjMRXt8hLvNGSAfOHMQj7knQZn6IKz3s3nIX+HavWGSmaTFYeTMFKNJAYxbgjneHwnRz73hbH6bSKwpuny8GXZY7+AskukrB/6PPkA+PUDP+1gLuM/nfE8s4fBsFV7Jiaey1sFz7vpmGt+F+YReWu/h+SSsB17kJTmXiew8dpYvGyBlkXi/2DS4bpQI1fWyRY8H6xD96upyxP3yNNFDsN4Ke5fWEbu2SxRcfSIpSmwn207Cv8K6LTRPPxPe47n2kOA6I+rlDcaeoI6JubnLQO+D5ytbptRgzFVQltPtO7FufFe66IX5FwHMaZ4/nq2o8JsmwI1lF18I+LUX1uJ6ZS2ArxjYGai8ISsWH39A92ViZjW+F2smZAR5hDN+x/uVRjVGsciLeizCt4l7vZC2B7AlHjwPtQ3PNctl+k0Tfjq+M3xBHiF87wT+8VLOXdJnXCrC2k8cGWIJjc25JzIB4CZcewBg3E1rGYwJ52YKZxfSiInC2e0UXKfFl24n4mj4Zj40NR1t2EzfvHQFpyYH6JlpviirAYhztiv+8TzCF7F8zzkJsUQz8Zxe99nuddA63qOv7xjCuC/M0bzIZW1TcjDb9fmPo995gcYlMhxfTv6t1FL/JKDmY3aDnAV9gu65dYM+Avp4ZI7nRukoyXr5OPyHSU8InqlP+YGq72k1ufovq+E/U3wEmIeHZ/Ph+9tv2UZ100VLxtazLRyrQbDIE69D0jzENiUPUTevNuX8R/Q90bovXMV6D7e5F2m7CfAR3wO8jTSXWHwcWeR8sZTXwQTPXH52NUfrNlBfSK6Va4+2pu0aff7h4rHHa1XGm/WD+PEiHmSQbnr+kGl2t5P5V0gu27NA3E5cj7liANbDA3A6e/7w9aPeuRlztxKuEyFFNNXaJKyjgXggvHaDBNoQr+IU1ktIbKeW4tUXYeJI06475orGZLwuh0HnAPo6JtYuOOZodii1z5xsHZCnIC/x0DFqz4bGeBbWBHhNWx4+R7xve/fPXeEzP3VMbBjj2Waz7WEPmdaLec5zSq6XClLmLSkii53horKqbE+nj7RclKDXNrmwRiRPuh7mww6RTwtSeBKOyZducw0PMrFPj6cbaaxfeQLtF0b47mxRjd/bbUDbPt26MSnoxvOhVoGMQTzkO9NpjBHd3+y0SV7COZdfwfYnUX95ANZmuS72T8TYv448cQfK2OKCUXo5f14NLyj8EmOGQY+LlCvxMDnJSvyfotvkJcT/Ya6np7tM8iahfZIN6xkfD25JqqsmAYwpjThmTsuuQlvUfMvdkrV4w8NY23OO6zDwnd48jH02PxvyoZ1DPL8fJJ7tg3y3E3hkgWThInkwpXwvwKUg7a7bsU7RBveBAPH8LUQ8pfWZ5wXcy6/YVY37B9mROv9YczRFaxT5XBbhO7JFMhIzcU+km9Acvcj2su2j6C9rUTz9dXyj1CtVapZsLounv+Zv4uHDeOMvzpKfPpoWse5rN+EGwiQ4kp++HHGWTA4iL5zTPBv4IPfKcfgPE64exl5/pmQ0Hzxq1Pjg+PnpTY7jg9p+F/LL7du3+dX91CzP2PnpKr/MWjg6P10/f4q/RMFfouBvyaVi+EzgrPg7H+51nNHy+zHWvNnDxv7iIm3seTQWEXA2Fi/vp0bhtzL+ZKpHsT5XQbuhUePT7i+G+5UJ90feB5rbMBTkTWfO8j7cXwX3+0EPAZ2f1kXe8A3GeWGNumwn1lJj8Vc2CW0L9GXivoO6F1j+262Obmp7865ustm17YcMrg9zwT56Js/gp361HshVJQlxWNEjfvOlu/xdp7D+uPZcSkl8HNaSH4y29y1cfBzWhlObKC+YybnXW8A22XyjFocly5n25m9Qf8sUm75BnY5bj2uwvWiF6F4pL+Spb6Orl2/JE/cNYrztB7S+H4sfuR7shawI32ITWwaVvcCWiNiadp+/XPFj4/xf/oE6bzfNs4NruVhrVPjDVp/w9DKal3jVTZofm8+E+Tdv85nLHvKhH5vxvT0D5Vz7QAngtap3mi5nOijKi9rTTF86+HUNH06yOLu+xrnZnB5aR6o7vyDFtoR4v6woIhGHtdhWFS4CnlW23WfOvd+n5v9ijucEzOcE2YZ0TcjJOBmGtksLnuUzO53Ga4XcS4IsN4uI+6sy/HgGXGC+zWktIbTG71WlREeT18bLVcxVY+fdOEEvGkB+sOziu6oI2a/TmbgY5Q9h5A/toCe1g57UHkL+cGi+igdy+Oni2ZQ/hC7S+MPNSp1VHJs2Lh7orQzGpddbRs9xn7KXHFXqcVD+0avxj56F8fyjIYF/9NyY4NdEPCORn3UDzS8DOw1xBuOxWlJq3Gjzo++nG22z4ruD8J+L8nUN3OtS9lkwZgvtPbDbgzu49ojQ1wz0sN3PzrBEWW1xCg+9L4FuVh9mfs+rZ5lypNRu2xJ9TXIC/NMDdjqPPtKH3pPKDcF1XkMFrfEl3PpjaVbA5EsNmG5rgDbaoO8mLtggHHnSLzz3Wx/KTVo3qA3bu0Yq4G1LhIf2SMIfXvLhfhLaGiZSx4PdGkG/gsezR5xJHqf2QW1xWQTHRWXvdMy3wliIWWLT+UF31bX7RfVcxWsMWb2d8Nw8g3s96nYlhqzBIS74GODKnJK4+nbz7KtA/s+chnFOSx2eEpfkyZwiYTwo8qRO3JMusYoHLsc84P8WhVsXS3zTNeKOi4K8Xp7sg3755jmip/klqvvR+iQPvSlVFGvrZ6Z5zIuda+V1tMYWnmXtab6W9sW32UT7VHgPYNAka/IG99s8lSfhmR/6sX61eT97luagtuX68VwyPPP16GUMnxbdpPXXDLplsDQhtiOJ4TKNmf77lX7KMx6b4VPn0QY8roPr6RVeOegTVk/yWTiHD/Otr0iN3JZlsFXtTK5R8lg2DY7OY7m7sVuXx8LsiohfXx/vRMlZ6psrsTYri+LxHX1JO7iK8CU8u15pAJw19EQCBq63FtaYHdvi7m0wVPQ2GYK9zYbNvS2G9t42A9fXYcjqI0laDgvWd0k8C3y8fJZAcUGkVtn7JDLmRt9N9c9TwwG+FvAC9Tp9rAPiZBfcQ7nl8UT8yMOFwWNx/FudP/DvPuDfIMsqXOhrpPHrHy/z43lvD7o1GICt6l4Ufs6PtauRT5ZTHb5QgrHFHhinVsw+kJ+zAjlAg3Nvo+v59H/76LOVyrMrtWenUt50j8Lfss/K33hyRsgDGdaixGaHvhwdm42+x4ASm93UV+MO0PjicqpT7jw1lk651xdX//7GePyoPaXDj1fe9C3iE+otw3iW6+LjQvR7nRJfOFrPzUwHXf5Ioz9z5L3SCH0O45GVmMBva+PABJCjOn0a23tBqSWIvhaEAe4RDw2zWkQi6ERdSjw+8t41A/JClU+XD+B8aliNgffugnV+xYdrhfYz8K7VwLf6PM1T/ObeTP/u6cgD59lbp9dQ3mju/dJHfYYX1rjnX1LnFl77ksYnmYRyyeQ8JmK8hPDcMbEg9dhi9MsRbgG1t8TLmD0D+n5vOeAG2Ci5bVz7oDdp7sPC6it8wiudPuHjX2AewRyh7zU/82FpvM57cQ3N8xxlmwU026x8ArPN1lyAe5yaDoi5kGPptOjTpPsZtdnizROCcfZZ3gTMQ3eKqy4I0NzEsfZOHKlgz5MQtc0wBrd2IrPLehYoZ7IBTw3NvzuC+/Pqvjz60nG9cX++Yf4msKls4gS6B5gN97Jonh7iemh+QQxjbcq5zYM8196np6tuWL+qW0slzKlH+ymDRKZSG8qTJ05NQx0P5uTIFisvwD2a2VWe7g9F/G1MY/s0uLfKYv32isg/+lMDPI6NL8kTTaZgnN32XfD8gTNqDOj49ptOPlF6m3cm3n7ryUvQPwDXMRYGYCClBmxLSgzBhibAHeEI1qpY75sHOkAt194L4+sVVl/sQ33Ay23uKwc9HXAsvJyr6BOKJ8bJfk9bq29e8uN8A835fNWfmbzR3UD53AaqD5iaHJTHoA9b9Z0AH2xkPoR0mrtcaWI4Lcsk15tkehhxN7FefuYExNu7RuNtv4a3Jo7hbZR8B7zthzUG3D9O4+pd7GwZ9Cn0O8V+mkt3zaj1wbylCRi70n29eLOB4ep1ylrcLOvjK++ivPOAPCbvlBLXs94dv54bZd16gj4yyRW/nuIoey7dOgH6QrsO64ghLI4nwOIU6h5NV0uyP90qLLRK5uQg3f/B8QnFqbA+h52Iy5akvdUtoC804V6FdS89b0IoTpe2THxbwJoXM6eVVGHMIV/pFOdcOxv0rdlgA7UHrMXLH7aQbTRnyFx0MehbDh/xfBojnroB8y2zJRJ9ezHYvEHh1r0gs/fkbXAbg+j7IJ7UevR3zJwQcIP+GuTIHteG5Hr43r5++RWlQEdu0G0P0zrO2aV7JXoemyGrUUjW5A/OP1OZvzpfszz22puHA+7oqPoSLqVmzruMNsdYey0+W7+W2dT/+m7hOPrR32f4FzkT6PHkh/6mM3p8yQd8BhsSa7X0Ax9pUWJNX9njQ57SANevNzC72lMyJOLekF4/UeXrwzCmbhonJYq0HpSavwe6GM1lemi39JZDG4tlJN+JxUu1Uf7kAjmYJ82E8cUKxretm0Hv3Ccz2xrtaoT/TPh038Deq5VZzXrhTbMfaT95SF7I9hxBl/3D78GmeNWPtWAR5rXFNmcz2I3m3BJJ71emdgNvE5sGg+6QQT1P4xZKX7tjY9HXo6P45dyC+PVZG9Otz5HV/pdviF+fB2KYL1QK8iBffOEo+p/3BDAW3dSH8UdvC1Yu4uiXb3Sac98WcU8dcy04smAliz/Cenb5SszQbPp9+VGkxWMOjEnd18tqcrHYo5siJjLbif2w52+ifTro8+w7u87GYqHXIzT2aE0vnlE6Nj668xNqZX0dj4/t14+WDzuhPdlPnOg3w3oPqKfi+Tver9gaYn4f2sZ3po2lb909Km59w9c1tF0Wu14Ywf0PZluk0zE+kzcOzbyZ5L88YYzo69XL1f7eIL8lyuxz5DUN59XzKs9CuxD5lcqnzGWzpTnXpklNJD3fQvbkIT+yFt//MPF8BvypFvjT7WBDpFNf7AZ3GcylpB55FfKltWlYp2SvC/kR8iHz9i+prUti9e5Z5BopFWQhyMgoyEoWW/RcrQ9kax/IVNADg7XCa/2gG67yCdW9cTV3C1LrFiNfaQX5xvS8K5kPPVOViW1OHvU7jqOydznIZ9Bl+rxJ71QJt95KzxKcRaK+tTRGFnh62neQfajfVGaLrVT2XU9lX7PiTy+n+4qj+V84Df1LUbqPTfW1MNhNGUwGzs0b7aut/frb9wJKZDwXOt26L/Xcxr4Y62kJJ0VVpxOqwyDP0qzC0/cr9Zq6HeibR35lF34vEGudA2NKt0xcA3JrdpW1+JGHzbnD4pwZh0VzdotoIX8DeXUsD332zEd/YwzzXFUfPeKAihccudRVkHbH7SRQdu8G96cB4glTP33yJLbvh7IK6+O2gX2AMiu79NExffYNgOeZ1C9SGAGeFwkrtqr3NK5Fd25ed7wNeLa9uqn949C/MyGm7GQC/V+TEFOGtft1+wheeex9BGz7U0eC7inH6573JrRtVvQR3nBua7zzJNbD+D3Y1RLIjJ4B4ZWPfcLqi3we4ceScLIT4NveJ/szrBgLyNa8ydFAfdNlVcL3ngf76fpcS9LfH8a29mXUuIn17w7cGy83ZEXswgLKF2ZOu78Ka2/hns2ca18XrcWzqjwGbGM73bNZdvF/AS7cC7ZFb8x8zR7RfIcPfWtBEu1dbOH+kOfl/itfWFgmbXC/DXjwFuDBwnpxAuJBmp3pMCtcOzKU8+euKKvO4SrWo/7SBDKQ8q9FNt+FBqyB41rpMLAaOBjDwRPmK1h2cXZVMtjiGLOTjLllBrYPMG9iDY/Po56m1sHB92htT0NWfbcSk9M+RznHeCQ+rCkP9IJwJryL8WFbn97qvYD8XphIAoUsRmzjUhYjttHPYsQ2+j3dpbQOTtf5wA8MbO8Mx4l9YyxK2/kBmutgMXDQbhBo8RsJdX211oT3/Bqe3+EQy88PUhsBeIw10X+I76MuA+8PQjtR4bHrgU8OSq198kLU6QInmE4nnGC/d59hv3eCbgK815fKz70N+S71lQDvRb6b/PlYvgUWx3o2O9Qzpm736Ii/98R148gq0B9WXp0Yx3qJb8IJjY7Nb8yWVFo+m5/m5uPyQuRBO+G94HVn07tYDGPt55vcL3xeo+xpZNE9jX9cpZxRBvN3f9v7x+D9YyPvr8P3f62+f4zV6eEDNnFVP9YTrPNTfg96KNvzyJP47hvEcrj3E1Un7f5G1Ouj7dfp9dGe3HKuItpPa4duDvejLvraUV/+HG2/oyEJY6Pc9JwVzPvCOLsDyr6HcOS3ftQzwjR/C+20yUEqm8F+RLncoPh/QHePfbvuPk23vlbKzy6cN77u/sRVCWv70IfSqW+YfeI9yfBybZTh5Zoo++2Isd85oEd6utEv4BSPfxngGT6yPK6z6U3UX/xNjbvja80+UH1KqHdMTXmcR9+y6ku68Fkbfo+ZkzBeIJCLPqwGxdeO9IZnBelpLpPgGSCP3oZ9sbrAb1fuTK2hfih6Frji9zOPvZdM62P3XBMPs7B+//gPz/kq7PEw6/iG5dSN0hvHWCscE+qN4jdnl28VCf13yvFr1vO90fqt/RvU6dMjvGAVZ6YEecwzWPMl6JWgO85L1nQ5qseBDof8BHU45CmqDmfe/kM878eh1+MYv7dhPFe9ys9mfp0Y/3x5JIPsmYr5GPMMAVqfYST+udImmoDPeSoZniSfwJhnp6TUcD0rnA72j4XTRro+7rkJubH9OvisTvK1Z8fDZ0N/PY+5XCq+IY7j3mgsZ3w+kjO0yX3nUM1o+8/G3sPzVDCWgli3O3K4noBdmFXVRHORtlI/AurmqKObi9KlOd/bA3L4voexhhLWTzJf8y8R976YD6F2gAR6l2k6OsrdDqp/HR9E/fxvrs4vsS+zfegT3BMNrgt/Ii8sCJhuswRNPvxs4kAX/8M2H90jeeh9SXjtlA9raML6i/x5QV5du6GjCAcH5XczMQe/e4/C/woU/lcg8f35olGtF9B/ZtR+b3uOxv/Yfu/mXNwvKKc8EPgf7hv8YYvPadN44FAS7hls85vLXqV7voR8APbEIX8T1smoNEqYX9x5Bv2Rs2iuMZ5VhnnHnsoPRcydY/sZqRLm5fDDLIdvyxk8Dyb7coqL56E99oxfo8FtZ/VDRmlNQUWn7fuzP1GvRf145mktHudcfJsqXR8/NRZdM92ybs44dA26Zbp1NF1vxHO4/vCSj50XNC3CfAlGZzPfJJqfXSC96E7wJVht4gtA/20cFzGBrPFU3iqZ6ub6zL29PqzRfOGzRkl4bJ6P5jlzXKx1AOweVcf5+P/xC6+865sKvATpHuuxoL/q6An0M4OuevJdP8p51FGF1VN9wlFtPyB6TPsuLLwa+MiG3BL5cepzubDslGhKrqH+UzaXQC5fMls8fgxr/Hc7olQmp83ZaVjHE+tC58xp91WhPov5s+ZrDgMN/ZTqs3NufR1smufzsN6stTib6rRo7zBd9rOYhfsb6K7H8nDPGcfPbN0b64lndn0bh3S0woW66jKa18lqLnh71bzOPUpeZ7No6AkLuL/PkTTN5yGw3EIjmRXhm2xi84CS12mdJU6lPo90xedxI8vXFLKV52+E57NFgT4P30eul9Lr3gGW64k+jwMRDYYYZ3gK5C3qmBOSg1RvxpqIXUoNwgZD0N2tfF8L3y8ysJqIAUMNbzWwfNqpKTXuB4Bu+pU6ZxZjjVvVoaUZqg6t1UREHRqf/S41EbEvHENLcoDPpPX5uDDiEOKS8TTzX9R/b3w+u29wk7t/MF5fO6SMr2WQ4Ya6L8Z03Eggh+OCaI9wZLnrFFF9NlT3OGvdjJtH6mbIYQ/V3dyx7WW/YvlP2ePrwA/OTKDNx5w+cnIdj/iENdGItU9nh91IY+bi7DDXYeD/sxU7bK/ODruP2WG5kRE7zML9ndpgJJANtvgxkAWfURtsaJjhcO1XrI6DmsPuhblkkL2gzkfCfC3QVSqTwYFUlj+P+1f7cA+nFuMSnCKeTSnc+iNpWSrT/43cApqrHAA8Q/wUjjJf9XDascUjvAHXFGwgVRdoQv6wMCI2KXoB6r9Hv4qXSSiPqFxCeYRySZFJwuExZBfex1iL6lPSzbH4+9j+iA31WthXbgjCxN29Xqq/wLvVvcDT8nwo3zwGrncN6HlmA9YwvSKs1jDVx0c66Jnfl9Eapmh7GpAXE3aGldGQNajaemgHmr4avSc7L/nc9mSPJ+Ge7B3Up4e8PPvdOj+NZaHyBmzMLxLg9fH9fnVuOC+cH8IF54TzfuE45kyz/VTkm22gA+D4OVpbjdWeQju5qx/9HWzMizrKJHpmA+AJ8t/9pWU0pgvPXm1R+AeT+9lxdRFUHXsj2OHhYZX/RByM/8wWDwyr/Ge22DEcZHtjwHeLo6VVDbozORro2QyHw78Y3iviMzTP+JobpYb5BQOenDIJ6+zSOgklap2EiMh0Q4szNH84imuBa6KuB+aI4H610I97p68r+ZO/F7E9ep569qcinvsWnz+5l7aJeU8wlmjmsAZHWkujB2xTxQexc1jzQYRAf8Yx454s7sdSvov7ffSMApybm+al6HGrC2BpVngxxt8w3wDvxNgElmeercuJymL5CfDMe6VlI+e2IqwxlgNlgIev8+Nz+0uHxFRybCrdp8V86Vv/Jqrxv8tgjfgcxX699qDoVeYSgus03uPIr/ytabMkvQ53ZhbjZ61p94oPg86GfC4rD+U8jOkTlk9ezmpQ0HxyWIswrXGhrmHuTWwN1ToXABth4SyJwXuPbg0PR9GHM/8LVr9OOPJLv0c3jp8r48AYMgu3gNakiP4bZXIZyOS3QCbfDzL5UZDJ9wtsH6JYkclbw3zXlYosfT7MC1eKNw8qMtkyS2z9t34fQpHJXTqZDHxu6qAik7t0MhmuJw9qMvmBf7PcWrSZkA6RNpFGkVaRPqltGtHrfEGHpvfdL+6aLS8cGhzNr1GvRB2cBx08g2RcTu1oHnRbgjow2A7wPYfW97BWebqd9B7TgdPZPh/WsSjJpnvyeKab8Pd8v/00+lhKq45jDFf3Nj8fdor9pwL0nun02cd4CYyxH/RMVTeouCzRv0aobnCu+ZdIqw20/qfTp/FJ26Dmoxotm+2jZHPQweTzT8WqWaiPVqx/oW+de22fvLC2j8ndjZhvWstqi+EZe1sm3liF32tlVhfFU4txDYrt4PpMxLiGBzDfFPjO8Sg7g5PFyLQ5Ql+i/Xwl5YedeI5DiVUsP8ZqAOMaHz+p8tTL7KoegvIUdZFVwHvLFX65M8ZqC7XGmGxB3twcY/dZzYhILr8jW7SCPqrSb20M5Xq3A+m2nOOiNBZcod1Eul2g6EXwHKVdhBPo8VGk4QqHKqsiA6ivw/Uw1iu0cFeyfj5DurIpdBUBuqoDuooIKNM5Mluhq0/DyGPYvtxnYawnMzQcHKGr+Z8hXdkUuvosTOkq4fl99PnPdO1E6PVWep3R1dCnCj/Q1cTA+d07XZufRaZ58kGPJyIKt94uob5+EGy/clg7C/DERcBnEK4P4N4O2IVGA8K32+GhMg9rcXxGa0qoa4M+H3VNzNG4NXEgvoAO5sO1mYexklS/NNq7vwm41f69w0hfs2h8TMc3rPZAi1zj3vkN2zuk5zgqazoPxrnlG8Y7yhV6GJ1rzPwRSeTmvM67ihyYY4z5xZhTjPfwHEZ6jtdlD4uOwE8cyplcfcKMjSLmF2Oe8SI5K/ryNNW3MSM/OYBxzbbg08XsvMINxhreS9oHBJIFbRbnN3Ekv4FsHmwi7YPeQJkTc3WJ11ix343rubfPXIZnIhbYbwY7opJwg7W0PinxshjqvDmOwLMuUvQ7F8aGo816na5vwvqm+2MvKLmilfTsRpqf7EIeuIFeX5qXHFjqMJAZtB7+nJL7RXquOmE1nmGuLn087KJp6nlbK0SsGYDzo3HJ6TX8q1ew/ivJ3ZGx2m1NWypmYuwy0IntUt35PVjLEz5PGWrcAbffxfJQ8xJiuH/MajaToDIXQ582FwflWQiDuVeoMEjsX6DzesAQ4BuKC+saiqe5xqq3aQE90Whc515KLrEnJweVfL68CK2lPcZ4VgF/KyEVAx4SHAjNlx2h+dMiWHNgxwTkIxlO1BuQf2HOohnjYkBOoP4hLJwnhYwsr6S5y+I3P+sEOX+t9OKHFqlf8SEULyik60dg/UPz2ZkrpzgY//x7Img7hLkg9fN2klKp2UEkgnHIXA2PZ4yrbezm4uMTKG7QOq5L88oBRxYDjAA3Y9B2H9pbiEvPJ+3xc6TAinlZPIx5alyMQ3z9R3OvU8IzJ8MZuKdpc75UVkj3i8HGcR8F3iLLTqclKbva/JVNSia9eZYkeC7jmMNM0vNnTgO9MMPonDnNWJXtkMVsfhq8mzuYSQaiRvLRoIl8tM7DHxMt8Lt4wTQaxxVKYXWvrCSX+rUDRbKrOWqRsP0XY9qeJdBZL9BZH9BXH9BXXwvJojnmTbozHzHWF+N8R+J7lbjeuPi3qTp8p2fMM3zfeaaGf+syPb4zejeALjEWvjsvHo3vArRhJWiDZvXlEHcQcQhxCXHDXAb4cOttFCcSaQFr1U89D+wAsnmgofgeJ9YgQZweC5+XpyKNH+wj/VdoOdj9H/qj/Xv8vxi2SY6Sw36+SfE3PrfJh/wGxtALY+mF9nubB2vcwHv6gPf0hWkc0Y8T9tkTx5Ytzh8KKDT6Rh+294BCm09cejbavFtC/jh/JK+V+SYsIIMsBGOFeeeckgJpJnG/DLCq//4UraYV6vGzlDyMfYM1vAHWGNcex4zrj+PGNdfjwXdZf2ZP3uO0epT8s0WWuDxUlAW7LmHzstCxdzvWJhGTwqMiLEd1Rn4O6YmyWh2fhHH+jbdzIpMPVjvObxGFB8azFjei74LBBc/Mbm+xkJ4Q1lCYU1JC4SQakLcQoAF3PYulL4rYCffyHOAt8+Azh55LrdL72HxUoHzUMSbO3Ekwh77JkaSswaFJKrwLRmIuytG3BTiLsMcxDafZlqB+MUc513oHzYlJx/Nx+euV9Vkl16gyxVGXqcmqRTpZ9YBOJiE/wtwjI2E0r575jLJrJsG4QZKvl5k0H7w4m8r8cuXcTOzr8pG+cH3U/krx3EFXQywxPi8dz2kbyXefDjikjz9flJlQm0c5r9Whxt9NSajNQ+P/HHFzXEbneDfMLUOZG+9U6y8hj9fmVqbMrUyi+xPFpdQm25Cmzc198dhz09Mw0sNy0hNHE3p64M6ZL2K+Ku9co4snRJ9WOcZh3nKPRMx4vk5GvpdDfxrKA2PQSi6tJ56yoI+ULLHDdzzzGGEwfwB080DZvXZyR71jQB+fyOa14qLx8EPTrf5T/NiZosHwzIVjwxDh0oo5cOEC0YFnlPcf8uMzqi6Gso+eo0va1+GnFfS4eUCTqDNZ6DkSBteo878uSth3AH0D9agqZQwCKY+oMoOQ1YV4rmlyYKPLAHSMMEUb8cGJGo61KLJkVbLGp4W+1/21Srwa+nRf+Fqb66SEuRJlrrVfywuV+s5Okw7fvd/wReaibJpjlyjjj8pYK9os5YE+Dfg1gHySxhCdhVeqY0D41JnZOLhRNJkoT5ziBBojfd2YvGqfQaUfixPhiPICZGrMZtboupzy4W6HyivVnD9C3gT4CgDfwy7kcwbgb4zvGkHW9ADf5eqRp9rhO7RZ//4E7Rz0uNroQzUjMgjPxMN21LpMbM32jsR3TDLHr79J1vGPk2/6J02M5x/9CfHDnpIP/Xz/PJFgneCGUrpeiGsqDgL/r7fiGbSAe+hL3zwlIf94mOFb+pSx8O1IQXLgm1wDuWEE17jztfG0qrg2jHL2hgg7D4DN00Gw7gh9h/rwbVPG9uE7lFpj2yYk1M1XcGPlZHW+SYATRidu1dE624bRdF9pqHHrad6CZ9ecPOAfm+5ZjVWzQaOFlMlnkwvz7B4DnjOn8VDknxu/YvlU0BbVB2icnA7HQyBLkN4EwAcL2RwGfhAGuR8g5ArQue+G/4L8cpgT2nqLaV/NoBPshf9IaD6tvxKP+54SpxQF/PvFcJnkoDkf8xT/8DxphP9PGptP5snnwifx00BtwX2wpmHAtVDxv8PxdbFn2R0n0abPFnNOBtydxCiBjRObeRJrfuedBQc0fM+aNA4eAL5vzhgbD1aY4vmDyqemDo6/BnaQJajHqmun8kQ7rc9f0pi4pjNPszgUmttWlg14MnbM1D5V5im41iozXKN+1TPqmMZ+d3GUjWmN/gzx8/GD+Ru832f1zdB3iH761rQZI/IW/RBtMjfYIWfRWmej65w9IzK/hF8cSvqdC/0QFcNZ0da0jX613tmh1MTaZVUingu7QKHBTJIfQT7I8MhWh/AXFrqkTy/Q+RNAJxNgDSoDb7ro/gvxhTGHqTIl6K7k3IMpZBqsbX5kSEZ75A7AzxkxjHUblGUX040PAY+Vqx2BGldY3jVjJP7jyGq/pPQjy/IN5q/uktLJFdSeqmS4G8lelC51yRrdfl83Lpy3h+EG5ROVyTXUhrCQdhxnI+LYM+exeU7CucPvzxV44HlATWQztQudqRpvxz4i52t81xpAvQz1eITfc4XYZ2UAax6lR3iuAq6dgfd+Ff55mmaXoNw+yrF9rCbKW1HmeB3zMX4uZSSGOd+ko9lVHONnQuhZsJvy7QfoXOTC5ADCsDCIvKCS8oJCqTVN9i+7WK6eE82nsrg5WTvLCsePNZ+uVOZg4RgNWaCvhh8QsQFsj5kKfQbPT9BnCYMzjmH7gMTsVy7oiKVqdLpPlQOKD53R//QInkG/fSA+nzfr/LPQP8fyeTennoX+J4xN/+r90gnq+lxhH9FlAEcRnh5qO+CzxY3Y33wuuNpPah/Cc8g4YnWuSsMcsXT7PAPF3T6kuSYuy4F0hzow0Fsf0NvZ84BHbESmr6p6O9poqk4gGtja43rr4TFpQjw8eND/iriKMOIHjNMxKUXdn0cc8oudwGf0+FOfxO6rc+rE9ZLrHqpVfHwejkP902E7T6nTTn2nxYBnZQCjbJbDbYjHsyZFtgKOu1R5ES2xAq4ZJQc/Gtca6JmL+Pzepxnt7Xkax7Ac/ZQAz/8Mlmo9Mm19lg2zurTqnJZknH1Oy0n8nEoS7IRoyWyYD9aiHz2fjiF1Pt0ONp/eBpDJDQcoz8fr25V5bnsa5xeAMXaeUeul4f2Aazncb027y498R3gzGT7Rb7wtTOsnnNzjx7YLUu+7HeDi/3kWvovru0LsHEZdAfcJ5MJKoHNz2S4/xuvPnLarGnNP+MF4/W/mtDXVuM9tS9PlgJ+poTwYeHJUoLbU7wqRz1vAbkD+el2E9Vd5hub254Nd48wkO8MWsjHM+A8PY7/Tj+Mr5yqAblY04jiFI7V+C9C0hcuifg0PfP+zhbU18wzmaOC4z4ThnToPjfeYlu8B/cZclgdwXd5Iz3wpvUmKDo227+qMI/Ny4loiHHE9GZwzYAzpjQhrdrYcwjijkd1j16e/XVd9M9zT08bPSTwPv3Kkj+J8hDXDF3aWrXEoHl9YDSzbCL4gXiwmATfqkcLgMOBLYdUI/g8ERmRRe9roeTionLeNwpuGQbYH8YKmB3AB4+j9B8+CIpgP9W3F6QOoCzTIwYEukP+474B1T8OgAzTJmwdQ3qB8bwM9oUN2D3ZSPWEzrX/aD/qBZQpx4D7F3ONZ0Xe4nhHdoH14mMVPgi43LNfkeX+7BvSDVWL35KyYJcVW1TbRZt9pD/CWlDoBv7fAd7gXaZzVJK1Nspgaf0Do3nLq8qZJqUZiuv1B0p86oWnSnVc1uCekENMDBmL6KTGKslziFPgyqXsyFzmVxPwZL5XMh3+rhD5x8xTms1obmh5MAp4OtlRW90RbFeaPnpqc1Zh8VY17WC4qHJZ/Urg2qXvK8t/e4RJ+W+06I4PtllJWbUlZUQ06RnXbxO1XwTjnmMhGWodQKL5C2g38t5Os5RuHidj4AdsLTzVaTKlRGO/5MN4hiymQMvZ4tbHeA/8Pix7PUrFtotM+j6wQfR/algh/uE5qIAF+Awmx9g+P3X7DObVfTduX5V03jLR/skC6E3AznQz1WVJi1bRvjHl6bz49y7BdZuuXOKZKfAbuY82IZ5RnEtt9AXSqU5Pbn+6fFKQ+oOtG6Af1iCR7GOA+FeX15KzgrGSwtwO2FfOITcL38Z4sex0zk5cuvjxFjS19WJxpw71jsK05r+PeVC3mdAfg05AV5W/AcT70VT7FPeCY0h7jp/TESqZwA1iTxTMla8A7pWJAmNI+EJjSM1A7BfTeKT0f5ydrdO0BWYtyEeUtrYHK2erUMQkLr5EI70V+4KpT30mm9U5xTykXdGJf/2TAMw5jCB73CX94xYdnpRzEa/S5Nlq/UniswNc1mcVSCYNfAgxX+YW+V/0hmMPGyXgGNPBD06kZ5me3+fX1opYocEae3Dk74A7PrnFv327J376dz//DdlvF9u1lFeZnV/suIKVVk0vmSVeTedaiDy1VO8CWBxyvIwALL+mhYzVOCQ5kTgE6X7/Yh/UHTVPa609PrnhKSLpcFE7u9zfAOApSV9xmnhJcjTGey4marzrR3kH1xqn2Uxk17u7J7WGvKcuF+7tesrw68NutsDYB6qt8ZASu7PeSM8M6/bVaFAnGhM7NzSGyi6/NB302yEO/oLf4V4O8CiAv9JHq2wVXTKyl+vlEu+Mi1reQ0HdI1+/5Cf0eGorvd63MdFkv4GUtwPwZ3bgwTiw0qT1Cz62ejvtzS/1nFLhjWycMrO2C1HSaG9Sdg/L1332hye5IJshVK/H38f3XUVvP/JGPrmn5FQEe1jtISjLF5hnI2zOB/2SCDRF075sR779ruA305x8SsWT6JrcsR0HPSfdXXtArVl4QFY/OKqs6OgtrcjdcbS67Qcr2fCNivifvKKBnhICeNGgkKwbxfDUVlxGPNw6zGLZkjtmPGFsTVzcqOdPOnn8D5pEVEd5M8Ru51wdMXEEM/QEkGe2SFLuFez2EtUKMs7cKmPdi5XyOCgUerP3DLmu/4ps7wWxm/frOHAZ4rr/bB3gYEZ5b5wOcCwIe9gLePQq42Cf0NflVuJbYavjt272FiN9/2F69dDvg9wXEVZVDAlMnd63y85Z5YtGH1dU5pHqap+lp376hIE9j7557xGeeXicKC2dIjyiyp2UI8/YszsYfFIqNP/iLlBrlTKnLs0Z45/KBBljDs98vgfs549y3wn2ePOXgid9RP8D6zFPOm9b6fW3Ue564fkffz4nrd/R9E+3XD/0+7bhE6XfmQLw+11AYkPgci9icgrpuMuC3KYp7nEJSKtheLeGjye8IxDpHtFyi1IUMveFEHOC7AYc/kf1YGwpxePkFGg5bLtZwGHMf51+s2R8q/lZeqOJvJsXfo7MyqxF/zW/cICEuI+5SPEb87Z4N+Iv91wH+Rij+erD2IuBuC4x1Zurj7mbou21ycPXuye6ajsmb+zon9/QhnjSZEe8vsjfB/Q75oVxz2S0+sMMo3iHOdcwK8vOAn5yaHHwU8DCAuIj8DvmKhZ4Hwzsbhr0SLJTz7bRjQsMPponAw4MNt/1OqjShnV9VLfw9JramHfY13FQhkZZ0MWCyOBtuD0oNP+TEo5MQrqhPfJBrmowxL+jrJE61nm/DbQ9LDXN+KeWQGyMNN6aKDYUPw/fSWMPVdVLDTekib0Y4FTgdZHhq5QVgf19QIDlI2eWEbLranJsLsvsjgNVTIt8xU2wFGHlN3Y5KE+qCtsEAjK+hoEJquDEoGUF/zoR+G27jRCvOqXAFtA993J4uqnmMG6fUuFX6apuC/PQiuzGF8dzWtPd8HfIdMI6HrqDPwjXzLQ/5WmDtpxJtvwp+Y37qw2+nge50q01qmOzGdVkPPBl0okAurM86WJ9BC9h6XpPFBesEdsOjVxFyRwTjBmuTawCnr400bPJKDc+vlyaQO4Ky/EFuw9dTRA7HQwYCZvJRIJPc0Wshf+mzkqf6cshAX8iUFasEuDdPdteb4J2Gf8K8fxiUcC2a4BquRTgT1+IhxWeIdTlJiYOkhFvTsilM+UyLuApkTrbnYeCbf4E1fVTE63lG6xLcfxAWzpT4zO+JhH/Sb74lV6oE3tcwB8f5CKzZveGGr1PEhttx/VZEG34PsP0mXexOegZwbSbo0BkSawv0mJKLaPvYTwDWDPvBdvE+xvRhf9gX9qn2BXq3G/Gt4Z0KKWTiIg234dx4Zw5Jj+GaNvwQxqH0OcGwjgf9KOKd5B7APYE7sWY32BjlsE6taXvE6OQKehYK4jn62YRr3xM94U7RO2mzA/U11MXqopou8cD5AfdS8vjV8ybV8AcmP8MLT9/ngzZ6CcmxW2j981S7yhuODgbcB5EP5KSLNwO+7wC5h31umTOnyvyzDN8E0k/PtwlMwtrYnWHzusslPjRLbJ4UcGNuD9Y3Ah4Uw/weIwkFkCcJg7hu/WGEE/KIfvlvTvMt77D66Vg7IidbXDwYBDpZ42j4RQDeSwtz8B68H7LAu/eRtXSfggPauzNhP8xE/quvNe0W6eisWx7mM1209nd26KdinnHBEvO6n0q05rF1jZ/3zgB8SILnlgp4XoX50p+K5fBsw93Az6YRsZbgOpfAOj8H75YtweeIJ1mE56TszJ+i3eTGNoTvbaftYPvYNn0O2sf2sF3cT2uYxnjyTFrXxgT20ztO5Mdmarcl25cPaPSG94aGdflsP14qtenq8yDtek1croUcEzAfjuaIGmuQX0ZQP0LdCPWiAD3H0Fp1YmBY040wf+6kpvskZwT4s/HZ8jH47KlB1O+DjyKe0TPMlfNMxtMzPORxnY6xE3SMvAQdY2eCjiE6zsSGdTrGRpe1W9ExepiOcTT2OI/8CvhAEMeI9g7q0V3n1bjxOvIeHDPyH+RngcEad+Ic2bmoJLfydLz8FL63TVyu8y8g3ZnI78ITiB94VGEf0h/okVEv5ucD259PadAn4hkIno73GM2d3E1p7sLTKqzRXphh32JAunv6arOphvcasM7/tfadcE3l0ZYMrNH079WZoFOijAlwjPZMxN9LSq6gdeTB7gH6+9AP9Fdt/tke/wTC8hZESn+Hw+aPHvLzOdeKGycBfnap9OcbFD6+D2z0TZT+zBzS3zDQ39NAf9XV/fJsp7kM49KQ/mZHMN6ynyj0d1hPf5tCKPPuI6sljvqueedo+vs7jO9aoKuHHsYzpyj9NaQBfVy5xPyUjv4yrUA3JfCcsQrj0c1FadII/d1ExOXJSH/ZQH/NIvJYfI6UAP0VAf3xaZR/Yhu4XtgOts/oD55D+oP26LlpSH83MfpLTkb6uyKKc0T665erXTjXTDnIZ5LXQTf6GGjXJZZkBN24Bqqeb6U1u0A/+ghs6zLU8d0xb4amH02dHK8f8ZNH60cHJn4H/egs+j0J/cTlUep93TyJ2UctX9XwKO+F50KUFzR9VePOjGLupBds8GrXom8YDvId14ohrNGUgKMrv9LkwjK4367gLPq3sA0Wn8ZyuVrlTe4Wug94rb3kTA0/sn81BXlGtn0ZPXOZiE8XYyw/cS73WKh/awPYWA8uISMxhGuUPQFjqCiIseaFRcYK3GsBvhYrGdE9Ai6cL9reJmXOGJM5pxt9n1fYHZeiLbnLxXsux3oSPD6TTH00NvtBZW8HzzTEdj1TmX+tVfmdrPxW995eIN913IYg5s4VFpVV0DxDk1s37iZl3IH4cYfZuD0X4rg3unh+qm7cuxLG/cZqfHbmpeq42e+uSwI8lcW4J4wxcIDfO4CftaYVIO+lMd6ESHQtJ8D394+rfprDN+ygetw2F5/wzMvKMxa4JqPvi46F3XtC9z5e74Dx7ZhcEZaU61g7dKX6/bUjvnvV74NH/eiTeV/BrY4pPX93TGmP8GAHlkzhetEW90zJ6i2f4u71TqnoFaa09wam9PTWTuH6PDJxdE5h/v53SI9fjSECeu9tkjf3tslZfR2yu69TrujrkoN93fLmvrDc3tc/UlNVq6eKvM46VBNX/x5pfuqgXr4ul7p1v1vT3qS1UaOT20PC+vm+D1PlhfA9gPsn4a9reG1/hnhHyU267jb7lhF8wth73rm8hND49rWIT9/XYmnFODpgNW0ZHdB6Km6GP/T8btcIHjUxPOqegnjkBPy/RIdHG3LHwqPQRfF4NP8ifJeeP5Fb+UW8/NPrEOhjefmreP0h2KfpD7u5wJhyWIzW8GPJ21OTuUdJQn989DqaxyUMnvYjD42eCPLoA+mX/8+Bvg9z2VbgizdE8PzPMJVJma6GOSiT/gdkUqbdakR5tEZieVjdY+iDqSDnvgdy5r+qeN7C5FH5xSAvZi8x3/EvWrOUOBr8PD8zQR5dLOGZPA3XM3nUQVR5FNbJo0yQR/8Ss/mLmTyCNgRXRJFHs5dg2/Q5aB/bY/IoyORRpjLvy35O59cvb3XgHC0gi1RbONr/7X6c8fQr1K2av07Qb67tEANx9R5xP+C/RazVqPrHpN5E/xjLMT41IejG5w6pdA74YP5kmu8fX7LfI34ExYfgSNNkJKu5w2RkJqzj0fNVe5nJx9CE7+D/ivMfpA9o8tGQ6yE5dKw7vzwX2IW+s25a8eXZddMS6LM/ob7lyi/GkqesBqE3pcZ9Z8omN9pdqg3WBLqq+JW8EGtlY7z3jwxYGyLJfvD0aHl7Kja23JoZi5db5ti5yq0aPM/KhXs3iXIrakKeAfoSf5nCb/LGkFtMvoLtFydvN0Rx3+tuidY/+Xw4br9aUM+MNLH4nZ7PhuP27zEfCHkI+ndUnoL8BH09rWbV18M9mkMKV6OvB/nMWL4e6s9J8PWM5d+Z+UXQjc+gbEM6b02bCXb+mqno50/p1cYWuhDhdoUd83fQFxT9HO3+PX4HsV1uLsuVSoDPebreEtGHjHHPe5R5ZYIujnol6pdn0y2bT4Pt3KXwh49/Tvki+Rr5YhrwxRucR2fh+QfH4viidv4L8McCjT+2pTL+yOLGeWf5KP6YEscfy0f446wlSH94tpX5jv8TSQ7wSIsV6O9iCf0ri1FXn8N4o8ipvLEjgTf+H+WNG5E3WjBnZY8Y1y60he1ie62qnj6KLx6jfNEqK3v3io87+fT/dx83+rf1vu1H+obP6tvecIrRtvlSE9brcPLhHHHjFwH37gR5xuzPi+zU/iR8Lr6PMhHzM9EWbTlewy/uU+IOYC4Wck/EyNmor+zoZ6jLoy14T1D4+Gd+5pdz15ccB11vtdm3+zPgCwDD431Y37JUauuFz+81ix3D8kIefWDJXkd0MuZnm+o/jLC5oN7Hg1xEv0z2yhVilNqznWH00Xi/CADtdcJ4K8PEcYHYkYZ0ewGAb47TSHLqcb+iP23s/YrMFOTXXwC/3iMxfv2Fjl8/Dvx6BvDrI4AvxRIfUvl16QDw61htRF4YIKm5qEuintWaluzbMmeNsFWhEdzfeyBSA7Yv6hUBB+71eQLoZykG3NsqbpmzVNgyZ6tgvnSFWK/M8+Bkbh3qad7PVdvnHecShV4XA3wa/pqIW5n22mjNiKxdGxkfn5icxZgEi5PJijtjFi6v/s4v5YWI86j/Iq84OmuNgHt9H36q8YpVJuQVmXbcG0T51xVGXpHuZ/rNDVI0jHj1kA95bznwfj6gjHP1hT58b2bs7DrRcRJ/vlOifhRKUem/+yz0n3oW+p+t0OkxB+pJVEdKpH9FN9r3LbrRCP2DbhTXLtK/49vof+uY9H/w2LnSf824+tHM6Gj9CPPVPZVv0T0l5N3n96i8uzOm+kX3fcZo8M5+pD0LpT30vUwgBfV3fabSnjuC97JX3i+ibwb9Mg98EQSaK1iN8Y6k5BJxH6W5S2DITqC5gnr0HxxPG+0/2J2M9HYJ5nSCfpQBNHeJpNFbo0JvSRKlN/5axX+wYgD9Byhr5gGeIr0FyGFoY7eE9HbdEZXeqkTzlzXMzwvz9VSiT2VGAq1ViVd+ptJaez3Q5OAqoDV1v2nDV+p+0xVRPF8a/SnoY1F9Ki0w736A9bfxx9CxGn5jn87fOQbdhhV9RsWF6BffggsjckClX5QDdwP9FtSbB9iZ4ePriR9/6z7pDhhTR4zhhMrnmo6OzRt29Wi8YefEeN5w8PN43jAEMBbeK/UfOAZ4lqATTPjk7DrBUeU8ukR9IC/5/4f6ANg7Gj8IjugDO8k56ANoK42rDwS/kz7Q/O//XB84nhp0073uHiZPsfY3rmPTSXnhZ9wRmqODeywYD4JnDeFvrGPsCb0n1k7e7MDa5OhLu/Lf2rrO5JivNyephh9KeYZH3X73V2PLoczBeHwmR84Fn2vGlEfLTyLOHVscnczFWtOOihNIfwjxrlQZG1zHWGi74wLEOybrQf5HUd7nRKkOKzHcmzGCx109Y+Px6cM6GXdePB7P+yoejxd/pdIG40kPDMoLl/Sc3dd4APhdZzLoPU/fr+xNZdvXnKjh0f4cvV9BvKWHNZsU/TDOERrT4mknfDm2X+bUF/F+maNfqPbSdJ29lG4PgG7O/DI/1vllshW/zF5qJ3lTFL9MieqX+bHil8ke5ZdJTov3yzzwBdpJh2m+i7M73k7yfMHspMBkZif9+cN4OynnC7YfgzAOH5IXtqat8DPcbUObLrcJeGvT5GDYU8lwFvH15wd18UUUXzddvRbx9eAzbqZDHXZNUuAoJpGSsXD3gaF43LUc/M958Qsw7s/IoB91Ib7hGrFpKBi3/snDAXfgy3h5jfDSx0Nz/x4eMz5ctS+DXfFwM5LLgpW9Y+P3hTr4NKTG4/fig/H4veogawPfRx0A23j/Y+39xWn4PpPzGFeLsp7Rm82v0RujDU8U14/hwdzD48/n5X8lzufHwTDIz9ihs9OWfXiT2zrM/Pimj1n+FvoUUj7W4p7U9/V+8jWRsf0NreF4f8OW8Nj+/cDkc/fvv2A4d/9+NCne3zAzrPkbThyMh58xHE9HKz+Ih1/42Gj8wna2HRx/HWwfJK7D1GDnF3j+gMuJ8Md9+bcUmOL5FD+Ka4+tS3LXJnce+vWrZSkzjLQwrNDCHHH+UJCu12KggTs/RJ2g2H/6AGsDY3o7wuysA8xF9Jra6zEu0muqcCwzZdU/qDy35V8wN8XutX+EOMZg9I+P4+c2/4v4uX3//fi5zfxCw8/6hHebI/HvTkp4F20/9d0lCe/emfDu+wfi383TvXvJx2Ovh7qujQcS18MVXD6gvf/hR+Ov548OjKar0Kfywm7QoZ9R7pmnVIQ2vqe1+chH448pZYw2p57R3l+Q8L75s/gxvfVe/PunPtXeTU94t+PT+HfrEt5t/hTxvCl38QGckzvC4tbWSI0/2C6lGs83pXpfnKTGXtfuV+PWtkv4TOL95fvVuLWx7ltMJfsxbm2Ngyf3Oyre02Dn3a+Nv/TD+PGHo/Gw27M/fvwdUQ1/z094F+MU9O/+OuHdA4Pau+92JfR7JB5uixL7PaK9+0TCuxsT3r0w4V0R3lXjITEOEuMhMRYS4yAxHhL9mBi3fPyDb3vOTWMwdsNze4AOkj/Q7WcB75h5BH8zv0Zz19g6T6grXucJdOHYf3CWfShsq9vFzi1X+HTURnm/h+o7plzeY1L49Bzg03ICn57OatmlqHya/Z7QhXw6j8Ky9F/xsOz/lw6WR1b793TGw7ITeNk/KM77+8q71VzK6UoO6nTaf/Qsc+9OmHtn11n24Sap83dGWHyVV5t/JZt/VzLO/yGY/xRl/k6Y/zvOseZ/PDl+/uV0/gVs/h/Ezz+vS5n/JAX//xk//6ldiXM20LGRY2PPOfxZ/Jy7Pht7zgHQE+cr9TJxzsLCQsmk7Kno172WxnK/4+Q9Fyjzzjnrum8k8fO+8zNt3Re9Hz9v/jMd7cK6v/tO/LwtnyXK53zaTvr74/Devuf8de8k8l5PEM/oU8ex50CCvi3Hj6M04f0cORH+bO/Xe3hs+Jccjoe/4/C57P164/d+GxjsN3Jj7f0+lDsW7KOGeNi3HdJw7v334ue85VA8/1ryj/g5rzmUOOc3KJ63vTf2nJvfi59zw3v6fSh1zkY6Z1rTpzoiCa/80yf0/ckvDJ7xM9ybE2H5mHyucKtHGoFFgMHiAIXFLbk8P1nHf0wjsBAGI36h769+4ZVDPqH6awlzG/TwMSfA59R+hE8Ohc+r++Ph07VfBx+wM6/bFw+fHVSeMdhW7R9fv4j9fbQuYB/G9xk+O8d7H/D5z6Pe/0FQGNDwOfZu/Pu1A/H8tCrh/eVK/DraARNOafN4+d2zjEPhS3NHjeNHwf4B7f2VCe+Twfj3T+yNf7+bvos1Sl30/bnvjgMHsFte3pvY/wXB/jNa/yc6E3SDofh1WJnw/oEhfFdZ/4R3u84krH/CuzvOqHl4hqRgXB1A/f8MwOf5Ecx1wrpJWOPI5LFJpkuWip1kKa3xpeSw6v/i8vkC57N8PszTn/tlVpQD2Yy5/p0mjJs54sdcWDW/L2TiBptMbprr32ZqH/SYuAFhxiax3JQ14DW5B5abKgYqTcEBwbR5IGBqH+g2cdFaU89AgylrsNlUMdhiCg7uMG0eVPP7et4eTsj9F2AOvvCet+P9La1pD9OcqglK/e7G4sjTNJcquduVPyLL2nItpMLVmnYJ9VOgbU33oUEvNX/1tI+YNs2gZ/89t8aHNukCHbw7kgLufdC2+as3/Uk9B6sxr/norI3VNAfz41V+8yc/9nlCPwE+MK/XSMy9fPNc0VwzydeNsY/Ri8QSajNeBGzpawfGIyxPio9HIEnob7/I2Zq2x8f87Rfp/O1PKvEIF0s0HoGfq/jbbQM0HsH1tUjPjGfnaLgzuW0DJrIhlw/NEyuBJ/HdBaKn/6B/fhLYdKYCqxn51GtHfFf+bbTPah9Rz4jhnY3FpY3q9dazxBhtTIgxWnuWGCML8FwP0WKjTHTvv43a40Yqy3QxAP0RWJ9po2xyQmMADo8p89sS+Opx+A24FQb86wXc6wXc60WdEvCvF/CvF/CvF/CvF/EX8K8X8LYPcLAPcJfGdQEu9gEu9gEu9gEe9yGuq3geF08Ut3d2kT2ZQx/5Wz7mI98qjI4n+iCX7Zf9Noz5CCYO/eO/lFhOwVjxREmaf9yjxhPdTmP8zXegb4jF+OMZ8a1pvXRPFOtgI57QeKIrsF4C/FMf+WyaR8B85FhnGfMI/kfM9tzO4omgDcwfwHbUnAX6HM0huJ3W16bxRLcHJN6izHvGEyLumalzxHiio8kvP0zCc8UHzgR5T+0hGt+G+1roQ5ir0K3wWL7vZuBfwmX3iy2K/zvnjOKv1rWNMMUYUOxjo4w+L/l25jc76kefV0+HRqPzaP2JixSf2deOliHqX/apPrNO4LWL/h7PYzEuZsIQtD+0iVf9GRYTt57W7zNVOGaasuqfeZO9cxTsOPMnT4vCybf8KAseUfp+gfJwmdqVOvkSJz8sJuX8993DCfUiVJu8kMm/hPftZ+Lfn5vw/gTduz9PeJckvHv6zQTZN6TXr2z2nYNj0/iWwXga3zAYT+O8qZ3uUyKtG6mOxujdq9B7iaknRnNAQ9MRx505JjxvtcgLn3jeGK03moN0L1iBhibZPUSz8TLhOz6XTL50qs9iLRVoMzKezn8z1l02tUfCVL7PpWf9LNmjzr8Y4JMRvzaPzfC9/0bi2oCOQ3X2uRS+F+6Jh2+THP/+EwnvY//MB8Tef79jbJ1ffX/JG2Pq/CzPfrJWb6c/pciRNFJvx+voTlsq6OvtBGRuoFbOGkCZGZLdAzvkngGsBYy1d1CGN8gVIJN/JzbJwYFmefMA5tgPyySvRW4faBkmXrVej75Oz/1clqjK5O//NVEmrxCFyypBLvuBV90gXTXm/ZWwlv6wsDBXOv+vqq/YD9d/Jr715TDDQ4Ml/41wNcylulCWq11bDNXVfImL1owiBm+hBXGN/sbztryFHNlciDRrIZxry8Tq6g5yZv0+kl/Pka4C3C9pIk+CrL/bnww2jfDKbh/yjUlvaLGGN3MBt4fs6jV/tMrHN1wnvgC6kSyfhDab8oTBz/xYBwPfObRb3be+V/RywZGYXDx7dcGCutozb2nrxtMaLbLLkymILeSZAfPAUp8J5I6nYZ4UIk/m7iD5sbj9f8y/Rn0D7Z82rZ0deN5w9IjffOkGesYRPVPro4d8fPO14p3AYzkiFCB8m8lDtNZo7HVtXmYZZdASXxM5Oap+36K3E/xPSv1HjKHG88gWtSf4n4Yx3yTJJzy9zPd+W3ycpgfPYm6yifM49BV7HV3I/94aHnU+C+r/Kq81AS9/gWzi28hd63eT/PVuZdzsnOki7w4iDSLcEGYILz18rvurNja7Dj5HYYz6587XPXdQDvB3fcuYNsKYMnVjenEXe34NPZMZ9zKywt1KfUmgrV6grV6gq16go16goV6goV6gnV6gs161XgzWoEQ9Yqy6MUirnpJ5Es4zRNZj7LkP8zoRNyIfKbQA/dbq6d+ko3+uCOaRZD+QHOSR3pGOkXYRH5BW1XpaqHerdI+0TGtrxbKiKh0/8hqbZxLoWrRWANbhvmyVuC+5xj33uJ4m/UCTMtCkDDQpA00WilZD0M3osVA8zmF9+Z/kBUCf63pyqePFnRr8MbdT5QMXvqbSkU8sgbF7UyocxBgovOs1Da+QJ3ekBFdjDn4yjCOQgnkEG6v3l270rzu50Y9jCoWm16F+2p3ijiGvX6PImYAix1bB79pUtCFwrUtXv/7uXbdzRHIBX6lGuf3r3do4yEU17nDmrurXU++4PTuMeQ288/rOMmnZ9fdVY/4pyvrsSIGE9RZTOK9jriJDEc8+VcYNffVhvCde8yYHHSr+0PlwbCw0J4vjCzGPUJa7HdNJG/BwRne41j96TcXRGXY8/6w7Ra0NyOaUqavNtDxVywuwLChltQPhfgPeH6PGpCOVnZ+C69CZ0r4OaaATYH8gJau+/S+6+PqUIP9BStbmS4htpXWkjyKsURQRZUafuM4W0l2I64zrrb0/w54JvMSeeF68obtQxZODZwJ8W0K8spCMMXcWJwnYKmYlly0hJRm0plAomZ6/ZN89HOS7AQcwXnED8F4e2gL7M8+amjXgSK0YmE9sFXs4kp+T6h7wpnKDR1fbqpanZg1mpqLO4XUJC+dKTb+MeMtTewZwHbAetf/N9IqS1M00voLh/dWg89b5hIU3SOrYdqwGXQXXK/QstHGdpD9/XquVlU5r8Xgm1vDqOrQZwN7qyhXDBtCvYNyhZC7i4Uul/uSsGB/NFvGsJFoDcTDmx3y+KKuZ5sJ2x14/tAtAV+iIiljDTXjtU19/MvMlHEiu4bNe0+35Ah1ugPbMl2b6+Tan+ALo6hR2cfWBr1ttfsMmmd+o9sO9GO4Rb+ACDN4AY9Df3QC7CMC3F2DaCzDuBVj1Avx6Ab59ANs+xHd9PaSW1Z+sRntti2KDMfpMh3Zr+KZUVrcceSfySuSTyBtVvphYSwv5rb4+GdI/4KtLzwOGdPkzyEMQDy/5PwUOwE8Ql7tAR90xiHUZfCN6yBN/UvWOX4iLjo3P32YOBvn5oFtn/TVeXs5Ly15CbQby6Byse9EwvMm9kXvSPQv3U4EnTmKf/PU323yYu8nW12HHdVhD8ZrhA+KKiZ4ddd1qXH9cE1wLXJNV9GwuzJNw+r0kK6aPN6h//Sz+KaV+86QdCTo+9DtzWJ9/odYBZPysQmmvXJG/Z+MhYIe4Q8lZERxf95n4fA7kJZ1w/fOIKruwDkqVOB9oAa7Ts2mW0/PTGe1gPaBwEu/C9y2kuNq83+m/RIEztrVVaQffrbygzE9CjWB/3uEHGzmfNDzlw/bwbFYjeYJv+uWlFTvlZ/iR8XA/LqzV5dOaZnsdu5Q5HofraK+grYa2CsI2UT+auysevjlndPAFG+rlP8XD13Qmnp/dgzVxAS++jYb0dJNnjKebIWMNjzSGtMN9B9ph8KxxP7gzfg7oE6NnkJL4fDLk7Wdb7wkDrOY9yifpFU3OmYYS+LdSPwh5L91//z9VtgriKuAHPa/FjwXr4OJYePhEWGxMkAecwo/3DTF87E+ucOS/oq+vI4hTgY6G5elYt85hSm2P9T9pc2LsLJ4Ht+hV7VkrwLU8xR3MBDyypmAcWobdXGQbORsLzwjav8hGzz1qSdbwcwvoHXs4lDN8viWVG/C/aato+mVZRTjJ4oqCzMS++1Pc9eS3NidJzYot09HnufY3Mz3IV15g85v3ZvrNZU5/fwrmLV0iTiCo21vym37prIimsFymqBF1rRnVpxVYIkxsf9TlyT30pvSjVm3eoox7CmBzLcyRRun/f4lfDzzXT05S8Ht1kk+FH9bCQvzGc5Hx+hDMe4mytvA9iGclm2W2b2fe7/aT1GDYSyqgndzGq/6o0cj5ZKnjONLDmGdw0PqDdRYYRzrwVPRdTiDoh1nqAEVoocq385Ux3btkhdAEbbUp/AzxR9VPDqr1Ac6gvVLnQ3mPegDuZ6Fc97T9WTTvfUZEe+5z3fg8eMbapU4qLw8q9Tt3rDasJjSWPcCb91b7+U6X2JIaHNHH9HS8LCHfDf2Xn++I9zNMSEGcz7A3A17NSytbMgG+h+G7vp0NiO8lVnFNFHSD6gjmgazEXCW9XoI6iaaLjKWPsBqyfFTTR0wc00foGVFg03ansFxshMOnrVo8di3YU+ycnQvp3K2EzR31ghH9C3SDo9+MplfMMUdeSv1f/xePXztlHf8Ee3nly/H8M5H+X054PyAzfiHICDsbwA54RzLKIjaub+WzeKbpqSDq4H2LYexn43cHAa+MyhlLqjy7/Ei8PGsgmjwTdPIM9xKRZkEPLWz6pa3C/2bmUtQzUcap8s25Q5Nvb32SIN/avpt8cwD+A9+L4PeNp+WFyA8ueSmeR6KPTOWRyMM0HpkjXdWis0/Szp1HNut45EYdj1T5I+ratE/gi8Ktt9D5Iy9fDHhxrn3MT0a+WOo370e+eAfI/kt1PDG3gtRmipZk5IfF1Z/+SeOHl7wYnzdc+r/aHNeM8MNrR/FD96sJPlM9P3x6qc/dotHICD+E68Cv6xcofKRf4YdTVX64N8svVB+VGD90Nl7+Yjw/PDWs1V85J/7XovG/HfBul06f+zZ9pqI1fn4N38TrMz0vxtOjADSQDGvSn1IRzWDPUXsR57KMuOvrX9DgWgnyvZ/aF8qZQgOMVlsHcB6gm4IOjvqXyr83DrBcqauU32ux1jms1RllfruVc/T0+mm7Ivv7v2bxhiqvUeuzB19J8KkOxPMbLmF+OdAnjmmbAhcLjc16WFTbm5vQXhunwwfcv3hpDHyA64gP17XE48OabzR8oLVJFXwgv13jSP9DPE6Uw7PmUTLy3PDj8pc0/DBBOzkKH+sCXtMFfGzJYT0fE8QhoLuuFLcauxTBOuiMn9nsB5OQl/H5SNtI00jbaLOiDNL4WaZ/hQIn7OP0IdZ+l8rPdjRo/KyD8TPTWPwsQZYiPzN/KS9Ev454gvE44F29eL21X9urOBsPbwG558Dz/JR3TDEWt/qMAp9TCq/8vDku1pjWCsUz+ZDHT6Ay8IbIchnPFGT8E30NGv+cK32+XaOBU4Zz55/K+J0Iy1pDkNf7dwQD46fox0D4o29D5auqr0LjrbfCWhDqlyj/Drw1x4C8Nd1vfuNHkrks04/rShoyFf6KsitzKQldIhqpby+p+pGXNf7659/r+OtjM3yRbRoMApS/PixS+f+/8fTzQgL9nNiu5Vwy+ilX6ScWBZ36hMJf4DvQULk0E/f+Uti5t8IftviQhsxlWcBbSxvf+n08DUUpX/12elHXD+llN7xzVF//Cnj7g8oY8Ozo1rQqOq9LEua1hejmBXb3JdvH0JvhOvKFy1+I5wuhqKY3a3whl/KFE8/Hz2lZ9NzmdIluTjnwDsb0Y/+bFT4zFX4n0truPnkh6k6I78IQo5WVyvMvnGH39HoVPucZYvwSYZLy0jgwgbZStmm2YCKvVPmfCpOdQ+zcA/MbnA4m5RQmh7bGwyQ0pMKk7up0jLEnm9zsjOh4mKj9I0zuhHdEZY6/VmBVAr9RL5zfm7jPlhD/0nv2eta4V4Y+duwTz9gcOdfiMgn9dS70xeNeHO634V4c7r1hHWv02aM/Hvff0HePe3S456b66t1fan76Q8+NFQPjD7/1nOq/v9yOayJi7AdcR/g1ANwsKStozevFqVr96xL43ngFEdX612PVvt75rbWei+F/puTx2CRWu7hgSeI5AhhDwqkxJLSm8RVzXlVlXjLG9mqxOCwOp43WMNJicV6fgXEDaizOn3V0MSE54G4bicU5pMTi7KqmcTi91b54+bm410jm9fLN14jmR6/xdSrxOLUJ8TjNCfE4/HeKx7lGicfB/DUbjceh8TcN88QAxt+EMf7mkH+DEn9jUeJvtj73/9/xN0PfIf7GlBS//54Hv9tM6PvFuhisppK6b4b085/snWGdpfgYnCIvX6vEijx2nS7+ZrcSf7NGMJetGR1/M0vNT73I7qXxN4+ME3+TOk78zb908TdXjh1/cz2LvwmfNf7mX7r4myvPPf5GlxfXL6+Ji7+Jy0FU8Kl2/raBB86sU3LniiKWpG0PK3HcsKa2fJKBdf6z7fTMg5ISH4sjKxs4mnzLwyQEugPWcgsdFDE+To3lufdZxZ++/k6fSTlPQrh2r+hV4nn6h8bKPwWY03ieNY6bx4jnmaTj9S8kxPNUJsTzhKD94O9Hx/N0DNa4m8aJ5/nH79g7TRjP06vF87y6hV2/UxfPk/X78eN5NjeNjufZN6TF5PQ8H//+waH49ysS3t+pe3drwrstCe9emfBuaKQO9XNj5s3YR+pBj31/wkg96OfGzKs5HlPzapY60pu0fL+hWHwcUfJZ4oiOD8TzqoMD8XmvDhYn5MX8V2PoE7rvZTG5Y1h3NsfUHuNN3ACjyzanieYfWODfExnJia0sAx4wWYkfmpvLl0xS+JZHyZFgObHQVgTa6v22+CEYT8RB43duofFDF24dBxfWF/ue2JSIC1cr8UPXsPifLePED8H7SxLex/53xLT3n9gyTvwQvH/hprPGDyXp44daetj54GqcD+ot+jgBVYdB3UU9G1yWSZ63kHgxDkiff1ubpJxDAraTMKNB9FC5ovHPZG7Pav3ZvYQM9aFuZ+H+utrI+ftM3D19Vu53wL8un2OcvbV6AlnnflCZZzJXGIw/S/EK0URlWF6kWdmP5sjhh/ppHfhL7CK1MQWq/3jWafrPAYOm/3QYvl3/yTOci/5z1O/xyFROnqJ8ymU/yNXQOAisgdz826WOt5T1oNfem+/vgGsvK9dChnVuL9/j8uJ5Oyd3+3HuSNMWsrP6QUUvOCO/kSccWePH2BD+q7cpzaOOdJVCew3DBPji5QCarHwvno0FegvqgLK8y1XJu8H221aN/hR2LmbAhT4OI+kN8w4r5cfGQCRqImXOEsIXHZ1VB8/2hs1lGANhyzcG0iM8P1vspLFGbztQL8JnW9MOivis+hxR+m2TSRHOkyNDrn6YJ0deL3zrGTVfNPIQnntCAodcxoZqF9KqkbwOeLopjHzXBNcblWerjvzOP19XD1z/HO7PWkD/eFB5tl/eFI7Kr9N7P3pGjZ+Qb9hHfZ8/ycN438yGpY78Z1W6yApjvK+qj+j1jbOe76Q7UxlxPpNb0Td1GH0DbE2bYK6HNiryRB6f/75wZnz+u/bM+Pz3gTMa/617SouhE6nszQpjXP5/Oj/ENS9fQfHMpNgZ6vrhXHFNTz+t5PUO6/jKWOf/HGL8BfkHjgn5R7ucFcUzOk9oPGrkrOCz2Q5Pof4L7+9qVGrKkixHd9qRapxfwvlbzHYDJQ777zw4uv+Xlf5X6voXLlsmqrE100lFOIcEo5d8JS+ETxabOGO16Fb69hCW6zBe3yPzH6f/E8+M37/to/j+2xu+e/+dH48z/2/pf9v7CfP/D/r3jNP/iY3j99/4j4T5//Y/mP9HrH+UZeoYUMapsmwujKWSEAeeI4W+irvixiTSMXUCL99BNg96yebVyGOXJ9e4W8FWaCPtg8PyG4UB0j6AfBbPcrI2HHbVkp6BJuIeLJm2q9qSsqe6gWQNhgg3aL50lx/Pc0LfXTOpGPQ22Jx4RgzG2uG1cvy98Ab6PYd+z6XfefrdSb976HeHBAythCP31K2V6TlgaCvyBviN3/GccuG9BX7h7zP96PcuVdaN78oXu+n5S4N9hBTWvSfbmF5F/SWFdb9TfptoW4XsjGqYuyUlUo3ykucCfB6nnA31NbNLE8+G2jdKXlpBXtpAXuLZtdnK2VA+ejYU+gsnUHmJYyml87CDPaB+D9Fx3VNXr8wxoJsjnteItsKDG7W5WYHXw1r0Avx7Ad59APc+WIc+gHUfrFUfrGEf8hCM9/z5E8oeHOBSk0woPulr/o51Zrg6LivHxrVeGVcmp40L5sMLr7zpe1/hj2v1/kTcawW5/eEGXR18xXZm8XQ1eTSmrmGNw9O41FH/pMpzn81T7+U0bHXwcN8L91eO3Gf3yuG6ANd/lHDdC9dr4bo74fpyuN4A120J10NwvRmuT0q4XtK4xrEDrscU2I0H6w0wbxVeDmUdGxV4WXXriGdysbEsdWxW5Fi5Yj8mvv/UOO+H4P0K5f3MkfcZPhvPMPxuUH5HhzT8Pj7E3i+BeWUp73cNqefp8M7G2wrFxtteH3UezlQqv89+f2gI5ffZ7x8cQvm9iZ7js2edosMkxNMwXAD5rsq8MzpZm8HkW//7jL+pOjpH2iiPDQJf44Gf/fq3en6mnTUG8jOIz6Lt4CBBer5axTp1XVG2vkll63jnWy4HnlgOfEz1RQL/BBthadj5G1Uf8VHfpHASz5qfUXcV9DWV0s4MCnuMR1DPHlzwW3VfamneDnrm6YwIyxHA8xfZu8m6d6NEezdd926T8i7mcFrgfXVsWx9X4XAFzJ/FduD5fHi2wQTCzugSFuZL7BzFIlofCM+9tML8ckhFaB7BM9SyaQxza9o2PztbPZvmAWNfa2gd6SN+gAfYNMG+5ZTXtLnOrz9XmBZ51bH+aJ0KP5HmSYzMX9bip68beaZazFTsn0x69qVNEm69S6Jnd1LY6eKz0IeKPAj43+nfaPZhDsbPh2dI5ksP+xEGDjwPWvfsHt2zXXKAv+TJ0TH0DrDjVJ9LA7x/angTnwwwhOvr8wB29yrwF/Vx7Cmj9UXLe2fXF9o3jK8vOE/E6wv1v/nu+kLT/tH6Ao5hM4zBCmPI3zBaPzieoLd2ncU/25bgn205m3+WZMUwbj0HdAiA36AKoxKgNw/oHKbQT1xGuneYK6l+W6KvY6T4bAMk0WfrivPZQvt90H4ftNsH7cbFIR4d8YGw32vobyY7ncpaenU6eJy8VOIP0W+mj1ftWX8Wn4kSf1Dx60SfyR20ToJWbyG+vfqE9rxyfHuTEtrj5cT6DfHtuRPaIwntta9NiKcd1uFyKuPH3k4Nf5EnI+7UK/jLrRvNi9HGAVpdjeeE5ih8GPny+0pflRR33/SPxTdKADc8wKNUnlBONlP+++e6xD0ikfLhLIUekqGvDKDNTPLvPqR35CFsHIWIQ3X0Gtb3ekybL97Ha4d+reU8zP2NljuBeRcFqc/fPnJmN2mPrqxnfBm+w/N/o+d3Kud60/NlW9NW+5fTc2y3h6/axp6FOQEuBvtgLn0oPxAeex77dljg+unf3TGcyGcYfbe9c3b+UhEazV+m6u2xoKzMR+MxVz127jwG++fH6b/nN+P3/+H/Do/q/8VHv1v/bf8YjZ9u6H859A/tRO/6zdg4uhz0hRTcy6H7nm0umn+q9N027rro6jcDvjbp8LVZwdf0XyXiq0TxdeVatfZtocJrsR1bHeIXytxJv1Hl/oz8zKBtJCc0zNXEnR9fkOq7HeOEeh5nzwsn3/YTZY+Hnn9KnsurJBVR9K8tD2yFuTwH97eGG5/Xx8r4xADoH5XEHfFSXpmdT0hZvhCwOSspDteFOVIAn2UR3mITUQazOPeZdjxLnJ7JagnQcdMxwHri2L6vjgnWFGmCjgNjrWmb9w+ev1alsftpmweSatyV9IxtW34lO0c+hnbYzGl7aP2B7NK7JGz39K+HR86LNgWxrTJan24jhc1zeXi9I4C52m/C9yOgc+EzjwSWB952tAaOOZAm2RnQb8PnsUAnvZ9sh+tRE3kU1m1vdCbpDW2kOhzqTnmSOjfs/+dK/xgPzs68fi7PCGvUSeH7Jlyri1jJI+vt5N71zyfVSVnJgR9QPybQMOAI2BGM/ht0+QX6ewG4HgL5KAC8UAeppLkR/jDWtEe5uETjnxGBuGndUUJWRF8woF+2Ji9A3DEB3ukHmwZh/unj6vOsRik9j5e8uRqei3DAL48qMh7ux3B+T6xl82PP8070/+E8qc4L8xSKk7CGaf2vR/TOu/PbKAxxHPdHd8A6wPj7yuPyJ+B9gFcbPX+dwWg82IgJ9sKWiXUC7pvhOmyk7bIzvFug3xcoriAO2ILCrXfStVqcmJ9FeqkfE3A8Zgoec7A5/G39nl+rsHEDLLMUWPbCeiKe/DTaQHEqOx/tlU7ox/rUUuAle9a/vGZkT5vOO1Of/7da1V+Xiwoc61GXQdg6HxteGBf7FvqE7otfGnq2KTNkGDmbPBnmZb+xTYR3g510frPtOMccsm39VJJeP4+sePo6sq3herKnJeopkSqHjZKDLwPduLQe17d4wd8em0cO+30fHr6dI4f/S8XdPz+q8ZUO2u6e9bhWLyi5RiWBogjiDCGHCzODqE9lR1BmBtdq9jJ5Cs8ev1dEWrY9qsLBFz5Uo+ElIQUxbFe/rlsG4s+XLwmgTrmn70pd2x2NStsgg/+hyPrEdu4c0I81KybQ8bJxfvjY2OMM1unHtiI8t0ZPQ4jn6aPGG43F60Cj/L9/G8f/Vzu+vFuxdbS827X6u8m7zrfH8X9+S/9Vr43uP/879u8Zp/8Tv4r3f2dSnR/42Q6134ow6tx7arQ+v83nnQj/zrfGmf+vxp9/bHCM+dd8x/mP0/+JX47f/48Oj7H+we+4/rvHmf+39G87Pcb8v2P/nnH6P/HIt+h7ttH65q7Ad5z/m2P7h9qHs6JhGMODj4zW9wjIyDDoe8NyUb6FCw46nipzoszgaP4Y7quifyVvRNbXPaLyyzcLkwPIDwuCspxuT8xbRj+6mre8Qef7KX1E8980M/9NsJBkr8T6/PC9HuQL+hLyMRYcc3pR3sO9ChYXmBVL92n+1AdoDE/W5kw8K5OL79/CjW2XG7l4uzx6Fru8CfoSlfqEJs49mMlVDFo5zCNG3Yf5jkzULmd6kGajM9t8nu5Mo6EMtM3znLwnXcT3sbZJMslXfFDs+QMwHuinD/rpg3769PW7N56XcK4a0ep3V62Jt2Otip3dRJT6b1Kinc34Bax1n6rbL1FgynPfottz3KCRyxrEddTD5Oerdfrn/0vZ1QdHVWX52+mEdCKMwY0jKGBnA9qhWjdWodtNEugAShNgprMgBgPSIUETAQ0o44u8R3cjjmEWqjqDNZuW4HZ2zCxY4MbauMVUYVUyyAhurMIppwpqWStRXJK0UxVW3MlXp/ece+/re9/rfPkHFW7/3nv345xz7znnnnsu1XuWUrp301zU1cWoE9gprbMjNjr/XYzZibUf9zlyMCfDesxFx/x4DlperjnpXxcd20Guh83h9UC5/yr0T9cNUJ+N0rXb4UT9lpDPRvEeax3HNqCeq+tGtbQt/3pCyX8LZKDsBLQV/lWPnoX2dnd3Fnd320s+7/6jv7sb74Z/qAHH655Cr5ZFHA68T+QPfWUN2WTpQp8H/W9erRB4N5F4OHKD3j/ysHrHFvL4XDVqIpHv/gkpcAxCOa23TkEZsxDHPvuZMjfwM7xzxRXZEtXwbsDBxFr3bOthz6qhhxp+Z70CMvw+YHawjS67ehJl7sijRN19V15OZK1d3W0lOXZic0f+nqjXEmQVxkV5vPkqxiH4XP2qUtSn4t0Guf9QqiUSl4/hnSh+8lnzBZAXxCxkHeicZdo4YPiMjrdwPI3jcROuctzK8TETvo3j6RwfNeHFHM/g+IgJX8DxWRwfNuFjhOGZHB8y4Tc4buP4X034BY5ncfz/zP3neDbHfzD3n+N3cfyOuf8cn83x78395/gcjv+vuf+AA7+4byfWHkXfrh7vzvxX1Wru/btVZuvmR5TKGg39c4Okanhj0nZd6IRy/006pzHZBpmNgczG9LkF5R7nl6rXZyjz0v6EB3T9K4qYTzBfiK7jP/aaiGk9Fv46CPpvGHN8EV+m2jfMzlDS+T+gtxVzbaJeT+3apk+GjfZJZAuBvj7kHATeB53fjTwf2UHUnjGYJ+MYh/EvxXbyu4PYf9/bbS4P+hIqq7U6vmbiOLBYEJgLod04Xscb9DaucOL8gc8o+Y3qHSvKfQ+X+1tc7h9ukNtzj+s5kP8VDozNTMr/IMr/c1z+HVz+HeqNDJB/j5D/LzNk+X+Yyj/KvlL5gobyP5jwun0Tyv6nRtlfqcv+LZdB9ucVqD0o+54sTVmdqQnZ//QYzkfIW50oW4AJ2f+U8x7DoxwXsm/EgxwXsm/E/RwXsm/EPRwXsm/E7RwXsm/ECceF7BvxHsJwIftGvJPjQvZN/ee4kH1T/zkuZN/Uf44L2Tf1n+NC9k39T8q+1yT7uv/aKP80Dgl4Gvm7Hfj7w1+ImJ1OKOcdEHJ6U7LFj74i9CfcC/PMW6guTgt69H1f/N4g2Ik98I3t/Jsdo+xcGTufh+f08I4vtPM97ihpHToNuhLqaVHQ0dpJV/g86R3qhDX7Milt6iZ5TXsrEwbfWu3oYQ+80x8lXTF4juoB7aCDoh5wHu1P0AMu0/JyrZv+dWlDpvPHGC+FayjohB/eAfvXCtPLMmn/wDh/9Lr0+aMF5g+M02Xv5314nue/wH75SasL9RnUnR61+F0lB/Wxojmqi5i+Ru8s9vhJ1xtsr5PNa/teF36MYPgPfWx+0+dC1EEecupz3Waqq2ZS3dtC+uvHEk+5qV8N1gbM44Cx1IT8MUgKF6mb2Rljt8eVpd6B/+8cssEckQV6kjFePZ3YQlSH9iyi38D/f0I8q9LJZ8F0ku1OJ143fu8aj0EYIr3hQaANtv2jBl2vKg3B70F5Xsa1ongE51vBH9c4f5S8ysbnbZi7kRY4//qHGa/Q8l9F3v0vGibeD9L11PJXUveDuu8wejaG2X0bubRfWQ7MZ4HtCn+fWI9/W4aNz32XwOcyHTRXFI+LR98K9qEjsy3gewfj5uv6NEWsWTgO5xRBQ6Qb08OTYxFahucKoY/MF2d3vy3d83BbMcXo3jH2b99+U4zuHdb2viHJp5KMqWP2PPmPVP99Offft76WasttsDDfPdpuHp6vDvv159cmttnG0jAecwcdl6F3MG72qYbOux9yHqFxs41K590Op4Jxs1vkuNkelzludo1VjgPKgHUvw604bNodq03LXZWpfeD5JPCBJ1vzeb6i9tCX3OY6Fk4L4VoFa6rDx89F6rm80Dauuc/bgP7J91fVqdff0X2wpf1RCynRbT208cD6qvpTKYvRDYK9d5rfB3ROug8IdaG9+9iYtU+7h4HxxUx/cs/onVV+HDfqYzt5xJUrjZ9tBuN3xBBHNQvGb5ZbKZTHr4yOoc/Hxi/XIt3RC3+bSSu1yepBnhX0dW/arvUe0McL78GrLi6nNo+V5q2qpbHCWc6OTIemxN4P2Bg92DkQwKKWnmL8BvHf8v/JjW0o08jq7BC+W29lddfzuaPhQFJm3Kyu1SXl1AbMjiBtohZPCa5nxF9WhedRc8tKkjRKJIw0gn7EjvH5OEi6hhTsz6bVGvJA08sGv3QoiPuMsJa0x5Pzd5Fv3OhP1fPqXI0fLn0vnhpvg/rs8F4hl6pFrJNVeybSZ+tU4s1Uu8eEPtvwqug/WydWU1819L/pPSkfEetHXtOVl5J+1hC2v3Bcjz/qcUVWvK9FVqTGB783hvFHk+NHaPzRZLg9pwZwfTz1+1HOmvYDpqq/Jj51/WviU9e/OC7uZcExuLTXOAbOODv/j+tvDV97u5LrAcY85GN+a7rm6uNueWXm620HYevthvFp1tvBWYb1Vp3JejtoS663G8zrLXxPX28VWG91mXlyv5BNha63Os8sbYom+RnWlzjeGQnz2+oyt8NHQF5s7kfKieGOM5wDUFb3jEnriJXv//7bJP5A7pPcvi91DbnA976wnaf2ib2RcjqW3J9HmF8nnfvvcC5hcwjbh9Xv8dpA5xLC5R/naJR/nEuW0rM2Th47w/pnh/4VQP/sxv5J8kzjv5Jtwrr0eS0/otu7R3fLMeOTxmCxcUozrrfhD6b2nz5SP8F+OayhqDP28XjhIVh30UeGvlR9LhkkXSOgV40kEsEi9KGh3wz3wuMvsO+lwXs0/uGBBrWPxr0FXXOgu3E+5x2zRudehf62wxzTyfk88vNWDc/H4ZhE1rZqkWdatb+8LO2lhXdKuksBpVEup+0x1JN8WWqLJZik9YcvC1ozX9oZeL/E2U51VfSjFTnRz6bEzgTwvIhSNKQ603BfrZLGZtrT8DlrCT57nrSeaA/a3GcpTy9ywroRwr26dmIBWSxtWpweQl/naCIxz223Zh/MLXOA3VhWYrcWNCibKrRcei4R3s0ucC9+sKwBzyYqq3+qLfVVgm3rgDW4s2ipF2P+WouU1ffD39Jhn7cMZLR0WMTfXqL5yej9ZbUi94AjI1haPnglkFv2cQDjosDeCKFv5KbFKN94VzfSoOEl3Z/QNQA0HJjIn4LPoy6n6wwZddP7VnKkeMUfdokYwHS+HsjrJrYJ106kU27ZwUDGSxPTqmKcxbfaToL994IxzqJpl867QEdSFa7PQNoVMXlOZ++hHdn/vPG9rbtELGUH0NVO6pR2eB9tsrNWRkccQ50PnNCGdrAjnKb5Et8H+p9A3lAu2gLKxeyAPY29j7kq8F5epCvSFOnpAJsS7yxkPnUjPZe8IOg5ZDHSM5FwAU8tOoj0wVh7bFs6ea6E8lXZExrJrnAjnyFfUT4jC5zIZ8hb7AxskXaV89M1+GuX9Ojje8S4o7zauF1AfAvUdqqTXVzZkXky0Mx1bNTDBy1sbD1Ak+O7pHslJJscx+B2tX5mSo+LOahizNT8Wjk/7OtqbZzJ8AUSOgG2dhGLvwoW3d7N2taRqdHYhDCT+37f1XVaJ4zl5aRscP7G+y4w5jP228CfpXZ502A8e94IYHyoftYb62jaLfrOvr1ulI4xl5NyPu8i/5tlBedm2ff47a7p5YOuzdbsBlzzcG5A+UcaFnP5CO1OjUvtkeJSUecrHmNxqT0k78RNWHs/52PcQXPnnwzY6R7C0RN4juz2LuEXwThzF0nNT3tNWhtDL7LxSON+zGauaxRCX9txXtL5Fb59oEbwK81fzfkVc5DIz22UnsP81adeTO2jXeoj5q9WLKyP0JcTi6GP/Tt5DLIp/tFurVZwfU2H+VmXCxzP76jesALzebn1Pvgw/+mLU49vdORw6Y0R4/ju5XUfAbu4t27qtgeBPi0jeturaNsf4e/XxNk5OzvIzNadxvnoil+cP6ZnJOAZsM2aHjM912p6Due2Dnguy/TcsDS/YX6NwtFQqd36ooK+W8p30lh1Svlndb7fWjvx+qDze9+wyJ+MbThaZap/hzy/Vp3Auuykls2xGAe2ep52YwTzF3jdSENl0xaN0hDaUzgq6XzZqfEAnW2p/gM8AxXE+McXJj4rAHbCG/HECncayXLQ/Qoeo6qP79UZnhfAM1R6H1HXmbtDpweL99Pj3L1SnH+xtE+M65e+T1zL4/wxbtZlwVwnzGfhOyl8FoMWYXPftExvc7enTeezqFGZz4KdXcL9ZN3G90O9PsnGXzMDGz9qmYmNX5M8K6WsX6xhbKKXnjeKuubuFOsAxpLj+aYayd7Vx7qgWvD9Vfk8Ev8eri+XqsS3zuMc8kANlREFZEmXD6T7eX6u4XH/9LTXv4/+wV3S9ysSeIbiSgDnnsUPrmhYOrgD1vMyqivg/IX7OMoDz6v1J9torjk7nt/gOsjSwYCK5/T28hixPZJ/Nwr2bDPGOoFdHYa1bd+OZGxUfzPzLfd5pf5jvz/3i3btSbAxtMent7+941Pbv47xqe1f27iwf8PQ5kvP6W3N688d1+/Txn7kDZ+RsCEpXnCq9rmmsc/nTWOfD401e/TxNPkHDPZkfSubTzCf0UTnK+fC3OIDemVUy3PL/mSsSw/pwjMNb+B7GSjLJIS/xTCHwRfb9XlUxD3h2TzMG2M+m1dLeoehvSMitrh3BHRLsCd6lneS0tFrMPfUE8uIQvJGGknVSJiERppJ6wjMraOXSdXoVX52SXvWHIv8MsxN+/t2mX5nea/2921M+V0D3t/f93jK74rqgN8X8t9n0bXlF6pKfWf3PWonecs7Mr8HefmvQ+n0fvdV/sUkDDwizie07jTljKDzZBR0vZALz0K2bjf6k4MWvMuxp0j5xxWHaG5m1O1OVh9qkJ5zgq6MPmJ2f8ZXAfRNQFv60/T+gy7oBR5o4+84SC+N5/SQLheeEfJC3R6MWQYdvHWbdGe5heUtd0n5GXurJvb3u3h+xqpKUz5t3nZDfmnsA+hFj1dOdP/HV4Fu/f4P/tycStP9H1WpOkihSX9qHH8XZKPr18tI6Nfntor7P/KqUvPLnIb6Gsm70NaVjhx6d2Yin5CVzgvjoVLkYeDLfuC7AeC7AeA7eu8Y8N4A8N4A8OsA8OkA8GkM+DAGfBoDXowBL8aAX2MoB58/O3MZ0HPcFJJeegc39gvPrfVX8FzNcXqHSbGbz3l2GnMeddF8HUC/rkrd9yBof64ySfcY7RfVd6PLLaAg+oZ+CHiCK0F/xbwQPSvN+UZv7zDl78Uzu0gbPJeM+f+e1XVbleaEwzuilP9cGVC+eZfun3xoeh/3eKhujPfTQNse26rjv/27LxMtoENfDMwGWuTenwA+DpVim3O//uiQ5/RKdTOUMXdYSYXQJwtBHnX5NMvfgS3cLsjEfGT3PfrqmHT2cq44T1LfIvQpObbv3ueSeZ/7qY+YLHX66RmbUrABs52baRxddbL+Qtwv5XUW0vhbKzzPz1ytz9cuVUwXA4rreb6G82hk2mfF+sfmpmr10laRQyLp/9muxz9ie1aDjYe+m4FRbNMe+RyfdH7Of3LyeEfL9mniHZ9OjXf8/JkfF+/Y805q/fv4/lhoWypNvPRsC6MJ6BWlLMZuZxBtH5ybMHYa9Q0/6BM4Th9vETHRqDO8SuWB0SjvmeQ6PeG4y/TG787dLL6l14d1YT1YHz6z0VTf29z+1vc1jyT4vWpB9K8OxLRtugxX932xTd///7pYP0Mev7fThTH3wZO36Jm2ZtCxTp/Evc+eolClqKtwEvoGI0Z+L+e2w5LK1LG9QG0HNrbtwO9hWCfoGQHQKU/xmM8w53XU94Dfqe6HOh/qPeHftFHd78w2of/4qX3eU2QjdX11IfENHP/Wp8W+3ETjX1UpxuajSp3fmZ7bA22q2iTq0WVp4zTfNPOfv9k4Psh72OaMZ1PHpx7Gx8/Hp8Y0HyDtb5ezd+6G37LSmZzGt8g88w3lu2UkEWjbLHjv0PXEMxO1Ve9Tw+ap+XSqePLgPxn7V8X7t2Rrav9yeP/SoH/L6LkxJifDfJyjk8s0z/djHI9en+g73Z8+eYTycg5Z12/PeBJsviXObmrzvQU22MPOzhSbrzPFBttg2Ke2gg32jUuZd0u9Y72l5i7/H/UD183AB64B1edi+Z3OUptvCbX5bC1HXBek+tpnUN+xH1lfi1TfPKivOE3UV5g2fX0tP7K+BWmiPgfUd1aqLzqD+mZbzDb0ty7FMXl9SNeKNLzbwKpZnhb0vQbrcyNphbnFQu05PKuFe76nyo1nkQDvh+foeuEfN5/vhW9y3smoEN9WuX030fdLpvh+/QTf13mz7Rnx/QVJ+7HTFXkC7KsnUu2vG9R+nBy/QO3HyXB7Tss47t9a6Bk2sY9aOqz5UtuPbcd8HBP1d6Nv8v4OxlP7m8b7+5E0DznHpu9vy9jU/VXHpu7vNrpfXTWEfdD7i334TrKH9fHA/t3R83JtWqMVtlS73twonWUanb6926Zpb/E07V0AuD7ecntbDPb75N/fME39zmnqnz1J/bPHzeu6cX6PNhn3O2X9rXSTrL8dovpbYSbqtCy+KJwe8rjomd78fpYfvUTbu1HX8QPqd7MOg06+EnT5gn1fzmJ+HpxDvC1tzN4AfUSXbx1D+a0AHLGQCUNerOXYLhOGeUmDHFtnwkC/d4U59ogJy0DfAcfmmrBZgJ3n2A8+I5YJ2GWOXTdhePfgNY59bMKycC+YY60mLBv9pKcY9qYJuwttFo7VmbDZaE9wbKMJmwOYh2OPmbCf4Fhz7F4TdjeONceGf27EcpB2HPtvEzYXsEaOdZmwewBr5libCfsbpAPHjpqwXKQDx/aasHuRDhwrN2E/RTpw7HETdh9gfRybb8LmoZ/gXYbFf2bE5gM2j2O9Jux+vC+AY5dM2AOAuTh2xoQtAMzLseMmbCHSiGP7TNgipBHHnjZhDyKNOOY2YahjN3JsoQnLwxhejllM2N8C1s6xbzcasXzAOjl2xYQtRjpw7JwJW8LngT7AmzjmwvPO3+N56J6ij9el2raTxevRvE4w96/ziTjoCii7pXItlAukchDK86VyGMpZUvk0lAX/7yw+D+V+qXwZytel8jUoX5HKg1D+vVS2nap2nZHKdihHpHIhlI9KZQ+UG6RyBZTrpHItlLdKZQXK66RyI5TdUrkZygVS+TSU58v9g3KW3D8oD/9M6h+U+6VyH5SvS2XyLvRfKs+D8u+lsgPKZ6SyC8oRqeyF8lGpXAHlBqlcC+U6qaxAeatUboTyOqkchbJbKrdDuUAqd0J5vtw/KGfJ/YPyMOfLPSb9CH1SH3u5XQn/n1sm1r7cYdw/ZnyMdtAPT82Ij5O+9mT8768mjv9txPjf9an7d2vwzlnqX8d9shDqUK7rZWJfewxs7l+Sqr4cEi3OBBsT40YjvA/4uw1+O+oVzzvhG5iHsCPzeTX8mwI3zh3K+iX0fiNc7+MbJNpzf4btn6tdS57Sbe9FmLur9DDGasbaAnZ+n9Al/p6NBPrwneM8puuX8BytA57F507x53L4c7v4c9SXwfemIk/KNvtk+5Kr/OXrhT+gbb3RHzAEdC5fLfa9cL+zdEbfle9D8xd/Ke03hekew0quGxVr5WtE/pwwQd1oBdWNlAnGpy1J206ea62VxpDvTdLKOE4HpOct0vMlXt32D8W6TfYMnh2L8z7i/8vXivbVJw57DgM/bF8reEPH8Vs49tdk3TKdn39+a+L4uTyadzPk+ot34j3neuBZzFMk55vp4vTomWG+mdMkb7SdlCb3nM+TqtEw6Rpppvk5LaOdQI/LPAfNmx7zvs/rdE96r0ec96hF2wL33zHnGuamwztz+D71e1IeFDnv3Dk+nhl0v0dTZ1uRzuxeDrSv9bzUHVaRl/q01ZyX2pOSlzrXOl2eTcxLzfaOl5E6tSPzxQDaRSjnh64XPI2yjnEDmG/0zBo9zojFGEbW6n0uofEPPprzbl2AnXcp0kQMFnH7+sbZXcSYb/SbI3TPxb1GOg9IcB8H7yH+KuAZLFG7E+hjvY/lk/r3i4fm6Px2MT2AdS9cK2QOaDUAtBoAWsWAllS2gZ6x8zTHZCgGtIudK50pT6z6//a+Njqq40rw9Wshmm7RCCLbEOP4kYAjHCQENnYjCdDrD6kFQpL1gYWBSE13S2rT6pa7W0YCyZKJMyNPHBA2tgUWIOdjBu96d+RdMsETZy1nnT3MOR6QbYiFQFhJnIkInj2cHWcjJ1hv762P7tdPauyZzP7Ys++e87pe3bpVdevWrXur6r2u15DDzjbl7xZUion3reY4E8+BbdPkPxPQ354p7E/+PvayksRzdEHw9txUHOuXCubsftDRzxRxw5n9pvW9d2zu+A9VbvJ+/F8bS7uktJ5yk6Io7cDEbBc+TBtNkfZFL23+TKiPvl93x6pnDLi34u3EMfRWcbKNk8Aut2xMlv9xFx/TybLXyr31Jv12WguTCX5XOI09f2oQlj2X+E7cssMBVocwY/8kgOeZF6I9JPq45YGuu+zJusj1A3WRjq8Hu1AnWz87UPTOZ9r31fG8ze93Hd02c7184SY/r3P29NPx8zpnS5cyj9xMnLfN61u4ie1j3uTvZ7P3/53q91S+RmzCx39StqC+94ANWWKPnwmJ56z0NEzP9s4O9feZB6j9xPP4+XpcZnuurznUtnM/sZ07Rfo8gJ/JXyYmn4FQKJJzh8g5XKgDDqL/5PnBdZS57SS2b2zyNpmXPUbnbQJ9XtoD6Z8WJafZWdogpI0Xqf8jQb+fgN+9Bnv+x3awu/H388H+9grLyNmGMJ/YhGeBDQlvkWdLqu//FAh9P8vv6RMLJk+uL3im71f5harn4bmL/we0ed9klvjT7qxHBsBHKwWDhqubhIarBT+ycz4efLJoal5nKzmL64Frvjt+vV8SfrMfn0Fm/a+VXT2ua5O9rnmTfa7AtX7yndTRyfYdga52sB34f4EB8rxl3yTmIWtPTV1bVfVgvVhXP7FxybIpGvTa3tqU0OWRjGU38H81jYZOcq5zo+GuzrxXnv6HgXrp5sBc4eZa47Kby4VlN0FuvwO5/Q7kdR3kRc7cATldbxTuIW1HP4LvbfYO0mc4P9X0m4PVPwz1y6x+tNF4jg+e4dNSmDjDjc9D8Xz42ewn5sO56/ovlAfHw0wZYL++zuwBysCmpH5fTUT976b6j9+k4PrPz1N8rUit//uI/scM+MzhrT/RMfCz6/i/7p34P2jQd8gD8+Clq9wG8g3R9W7V2bWCYeNRnAeMF/I54dJVtAx8Z15abzI8MSUZCg7jN5lsoLd41uJnykCBSRgrcN89ADIYKMh6b6Bbzf884YnJfCj7Giuz6MYb3bw+XBMIqnPqBGHTUcnwk2/hGVHbGb3p66/sr+z73nXMk7W5oIvOSx4FW95tyzaUfioZPvtWDqNFPotuFHaavq7sz/rjT7vzDF3IL/k/imJ8+hvIO37HJ6gch3XIMnq+4vuObn5mIj3TbqJgV37irEXet/jNgNn0gefDclAvln3hvDT/xPSJopi6/+fO0v9dtP/xOyS8/9+dXjY1jP2/Ud3/XfGzCoeFX37LKNxNz9O8/n3C27fXs2frhsQzJ/z+QRJvBvlPJkNCJzINoDOGt8j80P8APzvzbqhj1/XFQtd1fDd/FXmm3zXJ54Gdcw4UzQGaLDKfT+DPzsH30CcKcE3A9R/n1RmmA7IIuBtgD1/emHjXF9+lTzOhfiyF9dKyP9WI+L+Mu1cZyLvFJ55TFHqOpihM2NKEb75mIPbS9qlJWHy4veDTTvz2hAlobZAvq+orXeD/bbkPTXcDD6BLdV1pwtkhWFauv7d0qtMkmA+T9z8eTMzbfIT/r5H1SB35RoeRnK1YRt5xyb6WKVy7XjS1srMw6fsc3fGzQgXBQd7nA39UlCko14vcmzon4medJ+zJVlWdDao6a0idDtDJfPKMPlPIj9dpw/KlJfg+iMzrjBkSdbYbaJ0C0E6ozldHWWax/5n2M3/4NpTxdx8UbbrTIW24fP8j3gNXV5L/VliF/A6hb3fB6bmF3Yn8BeT5M/ShLfGdbfr/p854ub8i78lcgLTH7qdtayZnRi67tmhkc9ekceVdB2KbO/B/qSiTyqlXOr3CD79xWnyyaFA4DvPsH3aSeTSer7pO/d1i8NuGnqLjhcnvxAQVei6rfx2fxxm7t6/j7wwZrk/hvNkgXwe9vg76fB30+frH8fkK6pNEvi1A/yuHOtVTMPJZT1H7r492f6yZX/lwPa+on1+AjKENndMHivA7IKfnFhD7tvzuwH4cP1mbv9n10T3794+SswAGCvA/FHfdx85YB3lA/Fpu6ROdS6DeNOFe0OH167PG6rooP3dfo31O67j30uIuEfQVdTUN6ruf1JdP6psQDJ8uv7tUVecjSXW+sja5TqCfWe97dV2C9PRqWrcySXWc6u29706BzZ2wmYTf9ZV9dkBe/NmJIieRzZJV7f/yITnTdoT4lN5o+6//qvuUAc/t2NyB8/9VqvmKVah/2QTzBrTJS4TNjy0la5GV6xHXZyiyp0M64kfJNwwLO7J+ZesyCQHwCXeuukeo6/4YdNwI9x8Z8L+Fd9Jnwi8/ZcsgZ+AfKDTBPd93yXvZa3uN6d+9E6Od9GyUHht/p7a2YOY+jRvydN2fON934X0JnZrD7stU7eG+i58DAGPqUywrG/jA+teoyvr52kRZr69N7JFpdRR9ENfTd+/7AjZbpZ/cbr+ep/7++ROdPvADwT8mfC3yiecjpgtfAXmbHjsyjf1QmG0gNnO6wDmNY3nQRs4JZTLF9uSpvidam5d4X2rVH/GsA2oXuvL4mDdc+7sPJgrRrjSAzqFduXz/bxvwDBl893mRzQS2YDPYAlMHrhXRHnDehsn/A3oKRLBtBnZewM/v4++jPd29URhYjWeBwFyGnKtpMqDtkJ/emF5Saxbm4rn6Mp4Tgu/CtTuWdp1R6NkEJ4VlMMeo68Z36vPZ+mzr/Yk9yp3Ehna/lDjP32NrWa3dF9lP5h+1qxPt5/1f9PJTNq57gNu0hvVz3wsDYEf/qRvnqRI7E+SiTbUnS97pGST699kavv9EaU/PbexG+h/akvUV89QB/T8yenyuegZsbteDyfaRfj8KbdvSVSg7lBv6zQZh3tFPSL9vfgzLw32BdGHTy5nge0zT9IzYdmgP/veu/de93SjH1unEmRfNqraWrpl9LK1heOEzchaGLf593tyE7N6exncyi9YTu6qx084/QN0wdp5enbDnWhrpD7OdFZGYP41EZ38/sW3dzPd1hlTvJ/5glvcTyfwwJ/kdRZyPdrLvKdjA1pL17zq6/rWRc3eNG/p6TOtPz63vot8s6520CU9OXbwvUY6iGMnZeDZ874/QDNrWrUmk43tOMUHpPvCuAnPKhP3h7xO9svrfdj4mymcoQuWDuDOHdpN1CsrplyCnhTmJtWwvS/tsVQJXx3DXVLhshruowk0dpLi3VLizDPefVLh+hjuqwjUz3LdVOBvDPabCmRhulwo3+l2KK1XhTjHcOhWuneGWqXBuhpuvwi1muE+/kcBNPkNxv1HhzjDcuypcL8P9VIWrY7hXVLhshntehZv6DsU9qcKdZbgWFa6f4barcM0M51LhbAy3RoUzMdxdKtzoX1HcPBXuFMP9/l6V/Bjulyqcm+H+UYVbzHCvq3CTT1PcD1W4Mwx3WIXrZbguFa6O4QIqXDbD1apwU70UJ6twZxkuR4XrZ7gl9/L3w/GbvQ04HiZnjCVyOBAdUDh+5ggn7X8tNnch3Q3FMlnZ8J2urEcaui4oGVDGd64duCG041nWJmHPNdwTfQfs3Vm43oZrGK434EI/dRquIbhehQu/6/gDuPBbegNw9cN1BK4+uJ6BqxcufC8f/9eI3xXB72vierIVLnw/uRkuH1xoW3fCVQdXDVyVcOH3Zt1wOeHC70IUwoV7EXheFPr5VXBlw7UcLgmupXDhd1ay8Lt+cGXAZYIrDe02XDfBjk/Bhe8d3YDrY7jAIWzB78njdyKuwIXPR/B5EP4HC5+9nIUL7f8wXG/AhedOnYZrCC78r80puHBePQjXAFz9cOF7XH1w4ZkovXA9BRfasckWasf4/giuwbX9tjcc2eOPRAUOuztifoytjnZEV/v8jwe8/ijex/wtq0Nhn5/8rPCt9ra2BQPR2Kx0kIZX3mqvx9vsXx0I+fzt962OBvb5BaG4ompLVW15PYQOV32xXFZmlx3gGbCM1dHmFs4Hp6utdtW7a0tcNWV2gl8da2klIaNf3QgNiLSFcusIkHQtTuDtaYyu9jZFwm2tq1v8LeFIR26Lp53Vx+9mp/O2RSL+UCxVOicLBloCsfpAqJ5L8XPo26KeJn8yvWtbsbO+qrS8pN4p18jqOFyu6hqGnol3VRSr5eZ02WtLIB6LtPkRz0Syg+B3Sa6QZ3fQ7zMLOTmhthZPToundQOpf0VbsvzLa7fWl1c4XdVMTqycfMnrCYXCMcnb7Ak1+SUoBvQiKu0NxJrDbYD2BIOBUJMUgZ96SIhFwh1SYyASjXF5Q4350oq44uXkME3coInnbUiOA6vtGzAO5fs5dTyetyE5zqgxTmSsoidxFT2Jq+hJZ6roY4EWPzQtzl9TxO/3dSTS/e0eb4zWSuKUNicnGvMFQijnMLtl9D4/1KAqnwgwHr/1+Gtb7YPB5wl5/YK2X1pA8mGv1OgJQP9KvrZIvBsCoUAsQed/HBS60Sd5I35PLBAO8RzZxU6JNF2CBBi+vk0rk8pPkY/zscKXxE89SIHEiapWlla66h1ypewordnO6INtiXT79hpXdf1WuY7FucqXbiutrqiicmmNhL04fgKhxjDEt/pb5MeBA1Tn/ES9Elf0YtqqWFhqDYQkYor8EWkFxTR3RCWUJ8TNQpwfM21HPrmFmhqxSW2hcMTnj8QbiqOG0EVzV7Tl8lHD4hD6Ih2sPFogH09VrurarWDSKqpKH6ko38CTtenVNc6K2hoqkATRTLrNckmJy7khW/gqEuXjz1clpFvJ6B+/L3dt7hrUL9ALiK9dk7/mgfz7HuT8bvV0SGvXSGvz1j7A+IdBCZWVBUJtaBFbW70P3B/0C2seyF2TS+ny1q1ZJ2VXgVTdnphEE3LWsgpzKu6TchqDsfAGTxuIOKeRqH0kAEPDEwx4oqiNFOlv8YRiAW9OIBTzR1rD0QDRppzGMOheTmPE0+LPaQ2TRJqhxRNrzvFHIiEsNQaDLycYDrfmBFqSo4+DYSLlVJY6pJyHg6tyKtbQMMcTzQnBmAXGSdwe7WjZHQ4GvBLp3z2h8N6QsA1MDPCRL1ExCPa2QDAGMYwzFIGKaoKUOJ0c8Tbnq+KOcEsraF4kn8WLg56maH4ivQQGmNsTbebpcb11VVVVVO3Kl3zBcKufj678eNV8XLVF/fXeWPts+aBZM7LR8fRwqZPzX+WqLNvO8Wjg62maxk88TIyuBAJtC4HFbgXZ4agJgH3nI2eV5PM3etqCMexa6PJguIkk55nj9aIT2VJaVlbNx7lc43BDhXVqfa6p2l5fVrq1tIbwt0ZQ8V1ZAeO/3IUM5jF8IOQloc/vVdkPUm51WUVNtaDOv1XezMwHi5eW8zh40Yoqp6uK2CaIV7tcW+qrXTU8P4m7yuNygxHm4yE2cG8kEPNnN4IU7nncE1wl2VYm2z+0vLneGXJdEc1fQbpH21M8XyDUSiwnsT/1xNj6VbRCtLkt5gOFrd9L64vHI9o4JfAGw1F/Qs8lbxg8cMgXd8HEQ0AP83aSONhKrzZeH22FIeNPovNS2xKPB6JA5dlL5hhJePRAqjibGMTjUZxU+CPxOBpZyNTkj08beDnEjNdzI5xEryokzl/QE2hRxelUQp3u94TaWuv3eqAzI+p64lWTeCP61r2JuMe7J4kv4iLU9YZbO9Tp0UBTyBNMxINRv3/PzHYl6vPHwANHNPXX4whMqletJEn1+T1J/dLoDcWCqnhroDWZPtG1JP44NYYa+cY8sSjLH07u9whMDiIx9PmtzO3H5cT7nupR1BvBdgAR1YO2llbIHG1rSdarqD/G0bSc3eEIKxdZV4+HmfOLekctjHHaJDUlBfOGPxeoYQXTJks1rjLXVjRgUrbDXVu+pXpl3E/8O1UjlBNj2yZlV+KkZUXbSmhLsE3yRFGnwCp3kihOjvzRaDxeKkVj4aCfxcg9uJRIuEVq8ZvZvPPPBMZfTTgGNt8RCUejOdVh7x5/TKqJeBobA17KqLcZLE9Uyl6Ru6ZxxYp/T/nQoqodMi565Bo3Lfdh8Ctg1eOYmtKtLphRCZUVZWX1rm2ucmbhqyvlh3EhTPByVQn3Ozy+lsVrquTKerJSpcCWW0JpCbgScBw1kUBTE3jKpmB4NwjC3+KPNPlD3g6J6Wy1H9dKfu8eMqeRcBD5Z9FzqbA5HAnsC4c2Sjse9UCJvtzc3F1A54QhMlsB2vEj7SDrmF2cT6efTK3QMdNRl2TP4+NQKkRvvlEqDPja4RfsBPzuCQSD0Y1MTh0hr0QHthRubASOZxnfUmGjj9FXEVMgtXoisQDII24SZtoJmqkSTIlU7Ey2a2hfpELiSuqBCG7Bttd7IhG4RRtObil9GayHYOrh8aHPiXL7isgd2+SqXUJlBKVGRmvMH4TuidEJenVzeK+0GyZ5PhgSMcge88ywf9KOnFhnTrgzp6Uzp6kzp7EzxxOXbzW1L8n5mNEpLC0HRkHr8Le4GH7LXIDZQXwxK8FBPXvcEsftslQoV1V1VjmB/mHgvxjsFzjtEPjLYLI9lwqLndhlLUT01WDyJb5oUfsBQhavL04xw39IhSAv6A8+y2M+j0iuOOGPSLw04a+qwZNJUGTCrzG+SMN3POx2lTtcu1hnID1xhXw1meQfGacUHvFHwjnoR6VZ5gEEzwQMsqZ6R5xwXOESfpnxU1lc10naC1zFF3W7BNm7R9rtgeYJyXrNcuE0EaoBPWOzWz4VUPllKBv8DxKXlkGwA5aAu3g748w76FRD4lMNNsGO96xqfiLtgEluJ0xwd5F8MIVRcZiY1yRkStrfhlP1QGMAfADpo+Tp0Mx5klTIpEEsQH2ADLPEiCO7EhtpuaQ8Ysil+ExlxnxsZnlxvujoC8OoZkLUzq9U8z2wRCFSCnSkihFpR7zHZrY36G/ygMVNarF6XkksjbSDt24XtY90bwrpiD0HMwYGK7DPT1BkQwt7pzHQlDyPlXYUl8kl1ZwPB5pmKdAoNeJADUSl3YGQJ9IhhSNSsycqRZv9uz1Yw4z5MTAFOZL1vcbTLjmkymBbUyAkuWDS3RZj07DEfJs2phAcOvySvSTsuDD8NIY2ol2C8jkTMNGXmE0CPxCIAT98J0o7r08qFm2KtMMTaYoyLyQItcFYxJPT6IEe8nPGwCFABNQZNZ1UGfBHteuGWfmdWUExlgyL20gOSAjYgSUJyie+PkkqBsy/pwNHGha3SzWvDsQNxeIlX75z6V1fuTtz4aIvZd12+x0Uu73IcKexwC3SB4enMqeVBrjvXTqtHIFw8V3TyhsQZt89rZiMgmBbDukQTmZPK6cg7M2ZVj6CsH/1tHJ/miCczZtW2iFcvA7o5wDeNq3kQXiqcFoZgNC2aVq5AWGzPK1UpkO5jmnlGQjrXNPKaQhPuaeVmxhumVZWzRUEU+u0km2C9L+cVkbnAf13p5UimOb0vgH1ZQjC1NS00jkfypunKGetgtC+UFHKFkC+UkV5Bh+GQjgI4WilotgWQlijKEcgdAeB/kvAZ5uiOLMgX4eiDEA4BeEwxvcpykcYh9B0G8T3K8oqCKcgrIRwtEdRPobw1LcU5f7bga+nFKUOwua/UJRXITT1KsonEPZCuBgkbXpaUQohbD+kKG9AOAXhBMb7FCVtMcQhzIaw/TDwj3EIWzH+LPCLcQjPQHh2UFF6lkB5fwPlQGg7BXxi/DVF6f8yyOlHinIFw79XlPY7gZ+fKMopCCchfAdC90+BL8T/N0WR8OCpN6E+CLN/DvVBePYd4B/C9vPA112CcOYClIPhB4oyieElRan5CvDzKygHwsUfKUrW3YLQ8FtF6QQ9yeQPwPZVCWntsuHODIOwGHUPriLrtELeYTUuFRfK3c50WRBAxML9cF2BcsjzZ/s8WbCny8txHgPXx0umlafIJBPwJ8STBqc1b6H8RKVVgOwfXiU6i/pd8+VpJRPPpt5urYT0kwbHQJp83Og4IVZekcflq6VWwQEZ7NbKgbTjRiwIqGqujF99yExTnBYBp8HDyCvofhp+E7sY6jxpKLYWAa1Ye0Isu2pn1HZLIl/whOi+6jshyldlinJYi0jxDSdEr/mqy4IbJouhbSMSjJk03PAi5Z4Qiwmv4sPHjY+MO8ysSQ5LBdy68NZpEWPHja7xLceN8jj0NT5ThHJsK2AsYTmij7C2jZCHyH2JVUiXKdqFt9vJLZXlAOQdWDmtZKCcnESepf2mo3OPpb80B6VCmHZYJ3rSaoGDCuRg/MrlsUujTksHIMoSCNmCL/N9DOXt/AaMTwPrHyzIgSU5UcAuawOUVw45S3lOp+UhVewZ3MNCu7MKbAG2x3HSYD+Wbrf2GFDy8kCa/cV59n6TDKWCBE6ITiiv7Ohc3wfyqHzJflkmPSunyzL2xYdjsgWabIcQCnhxXr+Jt4v19uajczvMM7JaxN2XZMBC9ahzw8CPCW0Y/qewxHrDhB30Y9KvLAZjB/+XAnQN94HOId/lwC2KEStz0KYPpgFp3UtzxB2X7fEmj11yQkJC4IyxgPmyw9Jw2f3SnBLzZbtFZj+ypfiyUIm6DbykPQjjAPut1NqXgY0BUYFAjhurB9LEh2lrPqT6ZwcKdbNZop3jhJ1o54341g/0ncjkbp1Iw6EHYwbKtWOrq81URA5LCZOVVcA6JhJllxASKw7YD2WLm5IRPTWBXDILwKajbhRbh5DaZSaUDkvpScOjH5bQAeSwuEFe5g9LLK4PWR84Ie+RQsYbHYNO6zAZUWyQ2MmYCgLdwEbQHSPTv+PGgbTN1h6RcOfuxkZ8C3K4gfV0N3aAbPFDvCQed1jwJfbTUM4PwB99wscFdiAOm1qidWLjVXm8lQ5tYQpIPgL6mHNaqVnO6sUe3fq85QUzah12LeSFcWvtW0E4Ke5eWNIN/MhzglnGPBE4KId2pxfL6SWMDxxTH/ziYnpQtuw6vEB+1uo4kmH8xHBwkXxoodyXKT83X3zx3PmR9x96970Luw8veNZ6JKPx4KJDC/syn5tfaz4nn5dH7O87LO3kTn7fuN3wrvyefMFOScs4qdiEhRSbSSJofi0UV0ZpxM0Ua7fs4TfiozxfMWYThFehLyfALo42TStlOHuogLZzrXJZb8w/uAgaTtsqniGc20lrgH/5SIb8vEV+wSy/OE+GIX10rnws3fnSHGOHwYw8Q53294Gpi/IvZDJG5TH5ssz6jovpnMPSdn7k3ffev3DxFx+MXhq77EL+sAHPzT+SwTuAji8nK1WerdTSpFJlwnrqolSDiTZuTxIT5alzbk4ifCQ1ofgvSZQVt6A8lkTpSE0p4KK2D+ZQ7fjVyjmsv47OPWnAxrp5NmjPEbQoZdbBA2m8hESzxWGqr650t1Olqhfef+/dkfPnZAsUi6+5TEE9EwemlbrVzL9h3lKwdicNhxai4PggELeDDoCRB5sO6g26rdGQuHoMpBlXG86p23ql5OCi1H1kPCCeS6lIV2Q27BOD7rwM3H3Rbo9z/3OrcC6pA2AK8WE6lJteku62/1tKfCe5jWW3amNFMq3rlvI4YfjXUN8mJlM7bkUNZhL6/GOYj5cNTSu+QuYDX5yXaKXL2pOuaeljcXtG+tyutgqkz8W347IdvVQ6U5LIgHG5qCIqSUH0FwZqCt+1JwwA6oJV2JysBaDPH8B8If1f3W3FKi7KZudi3+czKrhBjvfDIIpdn1aCOHl2k3nUAIwbN3pN4sVKQUBH59I5UCmZD4mNRHiB9y+MXt7/C2gY9cPM010Zc0JeWoO2Ae7unSD05+Zved6yjUjGbh6FAWJ51EwldNlOiyqOF2URD1OWX5z3zeSRdVlbrf0W1TpHL9egd/SPXnaRNvixYodlCxZeQUa++CNa/gd1vELPxQ+2vH+hEaNkVCOrPA0Ls5tZDjRE+M5dD6wJ+/8I83d817cSZInMcFbsOJEYNAI/O4+li38L7KI6EC24NOqAlFk4F13mMVlN57QEzGMOy86xkmPpbWacdJrH0GuOEVtYCP2ZBuvR5SKsh/DNgs3Aw5H5A3OcJ4zPZ7iPmo7NfSn9OE4QTooO68jXqTY55gRvF08+u0A++CX5EFjFhfbD4PSt8gsgFRgb8+Q3DeKnVJtgeCpPHPzSoUV9Cw9nPrvgOesLlhfN/fPeNBjvMSoynQpQt0d6yU6Md9JM4+IFmGdA1epCjsx/PoMWRDkcmHM87YTxpPimATiL+z3jj+ckmHDNxoS4/XMIQol0z2zpOAScsI6P2WBdzdaSR+Cqs+Jbz7Cmx//Auawjy2CFh9NJmHbKOG0FjQKnAouwWecc0AJ0LOBVXpojk4Wh+Jw5yVfYua8AYfHVAU53Qft/dnCR+9DC2vOl52QcxJXnK8zU7+HbdDeAr/5NinIT56BVwAkd49QSnjQ8N9+Jyopj2DpyII2ODeZY32SOVetVSdm4LsJ9jEKHovju4HqU8YIZ1bLEOjifqikUvO+4cce4+7gxMu6Fhj833wFt7zfZoa2HFjqh0bAked4ilpxnk6GLbOyOb2FKDXX/4gIsWOZj6bRUpvoNhxZSe0VH29G5x42x89B5F8FDjLtnJrbHE+tmJjo0DJTC0kHNgd1SZx53Whz9pq2jTm32rQcX1fVlin6qPBc/uARGC2hJl26jazqnpYw2TJtXLDdrqnaMy5YI+KJzW6DMx1mRo5dqKf0OtaV+3uI8FycooQRViRqcBxe1nSOt3kMXltrK7ehFYVSO2AnVZnXJgDy4yEmzlx9esIN4ROwrMk/cS6ulHINK0/LAofHsLtYmQETfBe7kcXxHCc9ebq9TlHdMzCfjXA7VzXnScHjBVuvwMvWcj/o5aiDF1+iiHyZ6skYlHRbxk0MLS8h8rQoaU3pepkKqPDdSAdIFhcW9k5tQ9zsNilKDa+KHrINPoqWdYVLBd/4t3U1QLX5kMKpWYasGB8Xg+0g1iwThgk9ReoT4+sxB1mcP0dUg0rQDTZ4fbK6apjKxU4Q0A0DzzOfQDAPN5OfQfAQ0zsbUNP24/v0S2CugmUhja0T06GC3mEcHg59RAktE8EkvmHGUHkt3QO/2m2BJJG5Tz1xh7elKeFhiuQ2zTU6gQOpnwWEl57eIlXROdxXZhesHwNtHjyrK26JqX81h7cExr9p7Asshk/0cETcjwCQ6WZLDQvvlYygn2JJaDrh3kZklCGeBpkhUycFBdoZ2HUuP7+xUj9HJxFZaxRW7tUHjh2vGLo9fpfz7oMzTYUXB/SyhxNpK9vtOiHHWwSUQMw9FP0Y5d7EUu4Uad8r/q1BOxmMavapM1qsRoGm+BQ22/ROgeRtofOmEH7JTgQxVqmTJGRK/zWRpYUIFZo+lt46VMUYtlTAzceNkopauW8YdXBBlZoaRLdvG1O2I3Qby2HvrdvQDTWb7rWneAJog0MS0NOUJmgmgOfs55aTdDvOfjlvTZANNz+fQlAHNlVvQvI3vvgCNbZ+inJ2fpMvDIu58geoWEyUDVa4jGrb9ClcFGWjins5Olh92TitOJtaN4w7eieoMO/nwO240LjXg4BrHznWOy4mE8tFLlWOXcYsM+ho7bdyZSHSSPBVkYxf3y2zg44v+EsYJ1aEhrkPiQ+b4qHOZ42rcgP5efPu4EbegYpDX+V0lsQ9LZYAWsoPlEIbQ/gFd2UEY96aZsoIJhJMsuh1ki4buuoqgml4zrABcSWtp+7haiNwYJY3WKMwkSi0wQ942tudYemismNske5JMZYv7WHrlmAi/DWMt5sS64oodbAzuMVcuhvH3gkL3h0vQfs4cWyB4mDs4LNvMcRMlW0LmcSwDbTE+P4kdgzkat8XPWsl+FbPFblisQu/yFc97MqQ8a00sXHDN+oLZQTYmUEWgz+gSNj7D5PNKkAXddXrfPnMDAqybQ1UJ8IZ7j3lLBGH0hKJk0H1S+uyiLr7N6WJ3Du4LG4D+zMnUYwL14SmgyRpUlJ0GFU0fUVtWnGzJRvsHdGUvK4qk2qM9afDHaZgZF5B2FGiLvqcoF8iDSVraScNO1gtk553QkvH/ZbCJSEueoVgHKW1FvCmo79lAM3QKbPhc0q/YApT4FhhPtxnGXQmlFweOG0vjCkfmGT7ImzWkKENi8lipPm4MxzUAl6KsDyviI3jIENdQ10Ca13zFaakgZlTAlz3fgHKD/0VRbHOSxseE1i+SvUsH9Hh8N5MuKZriSq4xHdCKMrNWGywCvrySdyeM/R8rdO+Z+Q5cOIAbgFJ3khocxDpRRynGhyLo00Nj8hVWx2UYxwbMSB/8EJQdUNR5EDR5bjEI9Z19HepL+M5j6ScNOAYG0lwvzSmHxoEYoXgyUq8ycY45rK24K8GEhymsljGntXXGohlsDRSfsVQQdv4E1nHzaD+JZFucagJmpb6PzjGgaY/0m0pgun7QnJASWDrxeyxqv0IGEMkIPSlqqiwj64TRS4+QOX/XaLwIme9mwhx4lCOFpaj/8HPzvytKlnrs7aVaiunvYPrbYJNxbee2Srgb8BZ5DiDooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDjrooIMOOuiggw466KCDDv+fgQEuhQHGB50Un8fCiZvGOB3CkrlCUvxrLJ6pKTeDhYM2Gs5n8cULRVoOi4+w8u9kcRMLv8zCUZa+VJP++2kljGE2LU6Yw/A9jJF0Frel0dDM4v2MXwvnh4XGOOc0AytWOMvos1icRYU7WHgmL56xFX9eXSDy8lrVcuL5hpckt2PqdhrO0/DzFRZyPqYV2l6J5VdYnKffYPHFrIBPWfyf/28rUHeaPoh00OH/EVBUgPFeiVqQybvEWelPsfRhafb0SY5fNnu6xPC2FOnNDN+TIr2f4YdSpJ9l+NEU6aavUvzir86ens3wzSnaX8TS61Lk72H4vhTpwww/kiJ9kuGnUqRnfo3ipa/Nnp7H8EUp0usYfnJpCvmz9NEU6e0s/WyK9F6W3pei/jM8f4r0CYafSpGeuZy1f/ns6W6Gr0uR3srwPSnSB3n+FO0bYulFKdKHWfpIivInGX4qRXrmCorPW5Gifxi+J0X6KYY/myJduIfJ754U+s3wZ+6cPb2SpbemyN/L8EMp0kcY/kaK9MVfZ/L9eor+Y/jBFOkjDD+pSef2rOFVQ9J8dVhMm9XejbL4DSWZfoLRa+3fMKOf+I/J9IIxbVZ7OMToM19JppcYvdY+DjL6vl8l0xcxeq297GX0eRYxib6B0WvtZztvryGZvofRa+1pJptoN/xzMj+DjF5rX7k9vXFTI39Gr7W3dZz/H2jkz+i19tfN6If+oJF/Wtqs9tjG6/u9Rv6MXmufsxl9z2818mf0Wnu9mNEP/lMyfQOjn2G/efm/SabvYfRae87t99D3NfJn9Fr7zu1537hG/oxea++5fc/TlD/B6LX2/wyLF13SyH9O2qz+4BSjlz7SyJ/Ra/1DP2/v9zTyZ/Raf9HL6Ad/rZE/o9f6j3ZG3zqikT+j1/qTZi4fDT+DjF7rX7g/GXpZI39evkae3L8UndfIn9Fr/U8ej/+DRv7pabP6I4nz/xON/Bm91j+ZOP9/r5E/o9f6qxvMf+Rp6BsYvdZ/jTL6odc18mf0Wn92lpevoR9k9Fr/xv3Z0BmN/Bm91t+d4uVr6CcYvdb/9fHyf6yR/9y0Wf1hD6Mvek0jf0av9Y/NjH54SCN/Rq/1l3W8fA19A6PX+k83ox/8zxr5M3qtPy1xOPKl7JLy2pXSmgdy1+SukdbmrX0gb92adVJ2ld8nuT0xlpCzdiXb38hkBZfIyw33edbE94IK2R6QvAB+mkJtggF3R9IMQm60ORqLxDy7hdxQOObPhbTc3W2BoC8n4BNIrNkTbRZyfR2haEcLDWMRmvK4PxINhENJkXpIi/iDHiRkd63BmJAbCAXgN+Zvh99GiEBa2OeJeYRcf3N9Y8TT4q9v9kUSMaClybHd0SjNXu+JRDwdNDu/RxqsBUojvHlaAl7gJxyjSUIuye0Nt7T4QzEh0bpcTywWCexui/mjFKuK/7lgYXtP8d4Uk8PlGnrtbg7uQ/1vRQnzbHy/jYcZYvL+mUm7vmI8iJr9OB66MxL1GlX5+T5YHsOLmv09HvL9PPV+ZpLfZ3tlPD/fH+NhuiGZf414BBfbe+Nxvv/Gw0GV3MRZ2l+jSlPv//GQ7/9p5cfb/02W367Zb+Qh35/E/LfPkr+ZyYTvh/bYksOd2vW6Jh7S5J+wJYe2UcMt88c0+fn+Lw8/T//2sfxcfkUsHw+5/OLzVE3+A5r8Nqa4PCwTb11/nyb/U/eKSeHHS2+d/xjLz5cFw2w/e/immLRPnor/l1mf8vx8v3yE5c803Dr/38BlVemXNr9WX02a8L/CtUCVn+/Hj37B/G/y9gvJzxMmPic/h3eY7vD8kyz/JG+/mCx3k0YOFzX1Cwq7U2jGytkeiKjK8XL5a3q4kuU/Jd66/WOa+ofYenJIpBhbxq37b0JT/w0r889Wihn6HP35Das/T7svwfLnzt78ePg/Vc8uiL1bwNZ7C4xfaPyCVxd+z55FqKGQ5c8Ubm2/k/pOBWUsf5bh1vn/D5HYhOygFwMA' [riscv64]=$'0 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' 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' 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' [s390x]=$'0 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' ) +declare -A b64=([aarch64]=$'0 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' 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' 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' 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s6m3iZP/xl/6Nd56jvIM5afJ5776dZInsszieGZ7E2Emcw5b8wvVtA/rJ1KXfeQfXnncX2+hjqSR3NCrSVu/Q62zqZGs+EnGUfLoFhQ/xNSe+8xpA0zkMgU6N8j66gHfpcEDUi+Vbbu+1wl6hELhO/zjHx85WKIUPbib9yO3zhOm9oHfpJB9gaiD20TBaT1pP1o7CLk27M4granugh02E3FfV0EfVhNxc1dBHb8m0a/pYtgtxZ8el0FmsVQJr3uA/wFPyssX8Evsj5/ARTFo9/hqW8rzxhxLmIutkQyy0DxcytZaD4EeFrQXvbedM6YUxzPaQz0pSfSnEbCTzJi+6no6sIiij4FigHHaU9dvDzj5NmIr8Cf1bAzIEB/bsrPB277p0Z8MQ5eJJEdsR+58/TrUZxBPv8jMe1p8vQy4mYnOyO/Bq13sQlZ/trOKL/45ppIUUb7xAnoEPm4Lwdmqp9FAKz/HR7n/kmeMYZKm2h3TSgO1v+Kv313nzWmeA1PMR+61fufxaHldRY8fgEVczqzFKS/RcX7oUinDNZQF225i0HYBRKVCsstnYUg9Ti9c21nFkX0B3Gy+8xAHboWe/Zd8BQnqJbW+NpyeC3nJvlqLxkv5atNSmBQq4QY+GOJwT/2utwExW/5VwwfH7UK7pOvRnwzlYm/0H5nJ2zffwv+SWlU1Gql5ORdSkldrCKVK5sbcztBB/8QHViD+3Lkq53h99Femj/oE3jXlNf7AcUzaDi0hFkdzo2DrjvDXmmtjgWD2ljYpXLLS9BOegTejXpffw4eirJLrVM3uQIZSYq9XC58FWrW1D+9afWBlyavW3M+N2Pfmkvb1/rW5Q7ITCs+65SXlrjslRN7Kx4tyXNMym2XVuMpl1YfmHB2nf1M3rmz8op1gfskIApr6p4r43G7U0qVgAK9b5xoUdS1VV/AI8VePTG+6jp6rniKJfh0bpeM9PS8Mwr0mncc64zxgv7rVourfjKW3PGAS/3VMcKhXnxAUc/fr6hbFc/xxPCWKOouRT3pVI9qfzoM++4rntxWSSnLzVCkNVUHYR20Lw8BL0CBN/cXT12bvLuWobpN8ooSmGKzOtWxNmuF0xaHEq8262gwWLUQz/lAGU90q9rDjzhGOR4pi/ge1CsVdLInnsFHcsLPH1AvwSDP4rFiVVv8fm/4vifdnNdpmZWGu0c9pX12iId6AM8aH4buI/r3J/TqiLAACmY3CdeDlNdqedHL7wxBDLFIZDJP9ifoHWLIFg7jcdqsdw2WTb4tuZkATDvgAZrGk9JOZKYdUtRRtniErSR/j2Tf7ufvdXhWSw77L5Pioem/sQ/PGjM8z9un+KElGiyS/H3zY2NMvhPPD/f3nci/JqA5IxEGnFyG66Pdf5Dn1ZnnFci1WdW92s8HeWb7/AnDoeuq17Xeot2SiHantE9C7fp2oP4nz69qR/1eOMDtZ0e1zzPah0dRJuDpuLIKjUXan45Qk6lt4alSZqxnWg2gyfdLJBMeMYyyZWgbAEzUMl/x87I+A1/zi+89u+xq8b0kmMd1Yof2qXsVFVZX+wUH4B9hs8LO5N5X7uyURG0Tl7UWkJSkFRzgJonykg6eA3vzG+7O/aeiligl+zvlN2QpsrMEdyEBVzlDf4hQMsME33oeul6FBijtFQbhqR2ojVKyL1bMJcPEc3yaG0zbSw2WEiNqG4wkUfBS66o3I+H1eDIejiQ6VFiJ/o8C5DNAqBe0CfBhtJQW0RT6716Fz/Zqf6bqpWTET4T6/iu53sH1CI5Qz7CSKzYjx/geTQQPYpK0El7DqW6XWpHprckduxQFm/CLLnuFSx5agQaxpBBchR+vGsHolqxPPoRrJfqndcjhrqd94liFfVbND30/Lai54KFLLVfw7OglQilLi0swBT8MeoDiC+bel7YlJ7w+ZVZFhX3V/rTf2GFoFRgRI0HTvH1LUXxyq6dd9m3TOkaOWG8A9pYzW0nZ7FI3upGo7zO7U+BPnblqe3j9l6J0UFUe8b3jiXSApZ5HnrACl7aHDXfjwH7ejS94N7LEqm+g6qXBabDqL0L9Zyu4/tv9od3IG5PhPSH7XqXp42bHa5kHw2ug8xrEXIxYA9n7FrY+MVt7eB9O+0UrLUTgKQtNWw9P++S0p3A74slCiRZNpIAR+427pG07IEyYRgNFKmb8ZMBecoBBwbEMRd1wS3ulIg8rpR4NfpmiR60nfxsWVX8R4Xy22H/ub9oiAilyhBDvU3tadH041M6Wl8Q41NNquefk5DyzvGSi5G/777ZAcGryEtKKM/KDkjynuGRf11ZrVcsbUF+Wf4cp72Gq99ajoJcfjJF9FciI8utjZK8FmG/B/qCpOrgSpaRl+KGCdSj3qtXqxpJ98QVAheRgpned7NzYqpT+llZ9EIYHT11q7t0wKE9dX9mHsmz+C1Kq7Ps3/YrB4wv+Kn5fEt/3Vkji+74RaH/fLy8l/4thMEF43ZT3Fb3guxfK2CzXjd/1KrE01mrTpaWklSbieixDuYqMstxhD9EhOTTUNIbWkZ/+S6IuZOwC1YZfEeZpXz11vWXvDJpQX9m7hJlSYlpNRtEUW2tF3U50UXXb4pxFblsb7YE9waBTXuK0tV6GEAs/oRZ20A8tFDmz0pEPipn3RrQI56NVa3doxiio4gDzWVWzxYEEB5ultYkxRcINL+MztCK4jI/DL17GBmMbvftC87pZzDrDcPNY1l4cbpCTTwQ/hvawsjU40f3V+q+XjPkjEMjBpeH9139As6Oa8CIMjF86wy8tJYVAEfSeJI+liAU8km8loy/RzcRL2NBYf1N4/VFFfCD0fdxh31VoH0dJWb8J9R+sX2nm/jNMVe/h97CfvOeMPtBW3P5SJL+AdUuTfegpQ+vmXQu/9LQwHKSuUyv1PRdhhdBlYSnZBTV4TBDWSgpDGGr9S6Bd6rqlRYYzDjWaZQo3Qm3/1YsMpXk9Q2uYL9YQlm9sa5C6uzfSUmbDb+gi92+McYTrYpXQ0k+ddDGmlk/gkYCv/8Y7IYnXbzO+bhU+OUtNYgNNl/RYNHHjT+y+yOh+UlDUwlswm6pPjMI1ws2DR6SWivbBC+H2AEn6vy8Y++R4MK0mrdjxgGOES70IoshJQJUH7gfIzdccvyMFn/ySQ12jqAerOlJ77cJOkkdk3xewosumsczoBBHotd04qzUolezC8mAs+07kDio39zHlFAy0/eNR2fsJvtSa5R5gEiehM5KAXoXPAj9IK9Y2/AYrp64BxqCSfIlPN/0b5SNtUehRUSYiNAyqnfakMZ4bm4wnpsl4vtlF42GoCI8BR6fl7GR2BGvsPZD91JEpbnu1XLjPkM+m8fdTje8/30VfLVBRq9phrIcp+vuFu6K/f4vxfRXa4Ffp8zQQ7Qh04kopX0ocQh5cnVacpfazAcXKZyHe8VeDjmgv8vfybor8Vufwt6hcvpO+lTdXX9HIeI21i6BW/5IqqDwfW8E3loa1BfgQw0X+FFvMZNmHWFK1O5LePOR4UOg8ACYFxxMBsUCaiiOFoJYUuNq03SDWu9VjS1HPBlkk7u5A3A3ulAMokMYr9lLgqZVax92GBDC5d959ngtj5FmLSL/Ksh+W3yiu3aEUrMbOjXE5/sZy/YvbDX3JgvrSM6toAS2wNVn24xPVqpU8fkUtA2kB5UjUv1YhVdMqt7PQ3AY1sOtRA9s/W+sd3d/V3N93MLoqVJ2ypHNpu6s+DskTtFbE0AWfKZP054N4sniI/BlhPUcqvhrZG4sQCq3RRy84TTHgCRTzV2tYxk0GPSwYj8JWKmpD6UpgAbqtgSqJLkMZsMZK4EEJ5SXFHViULOTW7Cy1wgmMqxPwrY4k+49V/Evx6VjFPhs7kAs/4w9NPi+ZMtNqgvFjlVjzdayNAirvGh7odztsyU2glbpTzmjqTl6WHrL3PdxAqdxl3yN7PiSx7CVT1c+07rHbCO5yD6IEnIziUSqqYul4cpyBUo2CYmc22288q0cKOFI8U2yjTblxit9pG61UsAxcTA34eeBfCCWKug2l3ERtyg6E5ArURP411qW2IIVlrKI+YNJvRPkAh1b4fFiegsn34KnBB0A0npeYTHPY4yhvYXLbz8oepO9ZKFG+Sox95VO2jmknqm4Q75cbKnraOrcaVAIjJVA3Je3XX4NBeHvS1W71jFM9CYiqpOzS3t9GK5W3Pn8AsHCTFJqelaenJocXB8/Umy+PHgNDh89XGPAE4x9I4wdJo1PaCZe6yR0YH+MOfJyeyE/jeHaBmWhrM1Xlhew25tuUkiNml38gSOeSAhBh1e5iAJe9IxsRucwgxUK1vDLX1hHmgZPAZjgTnB89xIW+HxbB5e9kw5kPV0cdq8ZlcEGB1q8rHf+nue0nJ30HkJ3nW4miFvHKqoK0dbx6sHbaB78g+K+R9KPIrWGFvHvgR8QULDPOSqasgO1mgHq/2Tpc7bGvamMTecYDItGsq9GEBLTFjNs61ZpWnFajfQtrT/52RaeRfuPniZ4ABsRpnWE6SGgUmLO2Dsfhj7MpvnXyrNW0SSDueLdIRNXir5W927Ey4IDR1sny9N+Jl2wEnQo9IRTPkWqCzIhBRf6UTxXnyLkxOXJ6l+K8zoqnOF7xlAJVq847pNhLZO/91Ftp/hQz+gO8JBkmpRJ5VjqNgOofpxEMjqH6JKrv1AHqs7g+luqtXN8R6vtzvZnq0R8Q6jtBfU+ut1D9Dq5PgHoL17eg+mKu7wz1J2gjBrek+gVc3wXqf+V6K9XP5vpEqP+R61tB/dQpUNcV6j7nutZYNw7qukHdG1zXButGQF13qCvgujisy4C6Hqbcf0K5LZZTodzTlPsolNthOQnKV5ly74O1lBX75qmwEVADK/VGcVUrBBGmK8ASzGR75HJZzmxsZ+N2+7EdlNr3YsmTdjGtuGodtcg9T6+kbdGfZyXBgDfztDbcGdOjguMjDflAUefZ0mk7zyrqQlsGetVccquLbYokALNGe2orqafxQqAAjqa12hIMBr67GIu8sEzxD0mUV4Lmanm7WjIhKfYvpWPUwGxGcPuiJKLZKGi71RW2bNo5yyho7QxkXQzGu9RiFxBE/5AkRW3puWTJTXOqa8n4NNZtkPWSfbEGXfBP6Zjk8qcq6kAAzlJUYfOqoL8+1cgLit0oL9SiQS6Zogfi0RAIY4pXAk5bajYylh5aen0w+Jc/oy9UTSSFdZIyFFhhQz7tjnXbkt3SBcUfO7zCvJZEkySY+Eo6DRaNtKsQFQGvUpXAYqpJC2ovbALS6o9Fm5QNyIff0uo4SFdbYMxuv1UbBX3A6HBN0NHzxrQtiOWpq1Aj1O6iV3mNaM+qRmtPbmJ5aJsf+6PWSdq2LXgmEMzdH/W6CZoCnU5SSz0HpjE/CAyWBkryK++RZs4dV32CcGSUgKMwDPgZANx+sf0FqxFOytzAyBORdcUDP44DRkXbCZQ5Vvt6M8DgSlwz4GFo4XT7qW2F7L0LaKqx2fBOjN7agFd5yS/XmYLh0ciZpfrkYHjagUI6Lns8KNp7grFN4XdpCH4DlutOSgTGRQzGKG4stM0WgPyxbS4B3WLbghBAEwV9s7IJUK/W+sHaBfIaUWLzm21XhOJPYhiKF1GHZlsg71LalrFufyfBAuLOs5G/YnhgYXyiSSiFUfZlZ0dYI3MXAl4QPxT7+rxjSoW51iQMmcla3UayRPny4SOw633IaLMS/Qm1d3Hk0ChVG/IznbEmIwRg+f7NVO7Dpf6bsd0KG/JwbdymCLilmhx4nAYN5thIrQfgpepVP+FGZJoAbKGXHgC7WTqsLwK4AN93NxEjSlbLtMEbjaGMg6H4dsteqxivdgM8wnEtpu4JOA2Y1x7+iTcbV1D/lDgO6V2en1jP8N5Ke3ZyFZ4eaY9spO/10X75OYw3VRHnD9rd4j3fS/z1HvBhdY+2eBNjyN4m49B2b4hCkjgphCS9CPwX2jCiLUQ/jaEyffYLSPMzkLn9AsT8AsQKVmM7pN9kZ6A5KIFR6BrP/Wozf44QGVzqmuF+rz2eaDGMKQsFaxNJUPRWlloNqNUnM21d2jpXikbK0FHt8w0sBRWhrUD2YtQPyPpu+/mJm/QyA8/IphqFrjEbQxb0YkLSFIGkiwwk7Y2mjxB+8oCN+SOeXmrErYuuF/h6oLHZjmv/XN+8ub4YGs6OxAfAZwuga/1KE522IIjOplVL6Pq+BOu1ATXocL3m/5mQo6gjHcNB7xZszPuRVsNyExCEuVitnlLLkAwsgII2EXoCfTQYiw9OamVURNR/Hn5l+Q6BvIBbKK+cR32hIESGYty6RdCBG9UtOcXJ/yThP6n4Twb+k43/jMZ/JsgpXloEL2DEHj60jJiv1pu2wVTV5/LyFwqY9FkYyCPUx9t4vOscKVlBNcHTGJgVK9WbEQ7IjKuWqeX5L5n6CnlmTFkToTPi5yCc/3OdQYJTS0hrVEqOtVC2HnW1mvIrSXL28pd2i2/nXpMzO/9Cn9yH8y+0lr2Dgyz+Ro4ubx+owSvzmfHdtx7HI5bezzuDGLLAwuCEi4gYYkHBxhgPfGXF8j4GCOXMVgIvSTRNIaFMAbFfWy8mqpbby6Z59e7BK3+I9NequWF7P2pGD6Fdc4RLPbfyYTwivF9RLwDcxUOtdnGtYVmQvRnERPZqa6Euf0ps8BHZ15eqNCVlhzIoSK6RbSQm06h5e+oyZA/aZRxqscOz767chLR16kZPieSUl8Td4iyKu91pL5l4Alet3AlyMWyd9iR+0KNJRn/LBV2Opy8doy5v+O9d4gjKveZ4Uvxryw2lUvY+hWRwWDK61+J8FphzR9H5JAHfVRVIs0OrKz5bIU5yy7Sp64LEFXgw5axz2itzu+anm/I6eQZckyujHnmAPq/Nx9YFq3Ed0YrB50dcdqtHYCXTtmC9bl0XPj9Sy9O2eI4Uq5s9pRln5Wd6tIF/RrSJh3/dbZLgX2cbQKpRcYBjI+IAx9xxiGNxGfYzE3+Cj3aKV6Rd+qzGK/Y3qq0JO2xLHbalDttCD/PicEZyypy4JPo7My6V/nrjcI2g81WwFp1o1tIxvSCif5Ip97NlRyyMNhLgUY8lCcVUxkthqQjtgG8qmnAPCbsUwVpg0FcfSmigz9bca4l45z6Un56W96f8yZIpz70MGf3KQpMDvRXmfUi2uI/Xomufr/j5a6KevsNPp4unctE8Nkdkq5UP8/oHBo2BNtqhCv7OzfidG+k7tmUt2KK26i4itVpGhfjGyjB9WBYT3aaH0eZtbf9q5LSdZZ87SMQ+3Ajhj4eThtajp4Lh9cuRn7EoCyWBMktvGkn/MbsjYqoNFy9P7kFtgG/FadPhU8Cq4vRehhyI/cQb/aAggL1wB61EB8+v0s+w8S+Knh5PVPyDeoJmjkePN/v734I/x9eYRs+XlIJyU3a8wJ8Ky7kzHL0MP7ueFT/9g3adkZiKjEbMspyFIuJZsYkj4eLR1GVN2y30E//A95VAn3dJvA9Otmg91iCtsqyhTopz4/wDk6nefIX646up/pOm9b9wfWbT+hVcf13T+o+x3lMmDeg5GB/5B3WEP3LhI0Q6R6ElCYaunSzF4qAbsEmF5fhpyaCZufHallJalJZnQiuRyCsBz5bws9jws3OnjWdv87O9p0PPZsNPzcOfmnKaPvW8eKo9xa0fDbd+IdRTNj97XDzzDxpzQMJVlbXyMnQfyoYiknv/oD8ZD/5ND+4KPehvPJhDD64RDwBLHkTp4qbV9PvP+Psa/j3mfYkOtvQOq5EfsT2YmMcD9xMqP4QNCo5rIFBrU1czlimAZbJ3G4ki/Z3YQK3QXi1DSSWvD2zPVXsk0zJ0NhaOL4OugzYVlndAaWW50qrdDwBR1brCMqOaZ1tumVxNgtOg8dXY9klR77kgybMwZiowpNEFIok1K/DU6viqToZ+7FljddtPyN5sejnPtKwNn2dveE8CqlyrDSihUW13yEsebFNu6YhDqLC0FSPxbsm9xRUY2iYaiSJ+5jf0kb1of5WXZEsoL3i35FVlwXZZ0UT2XjEu+upTeNjRqJQcjdHcZUgYLZ9QFXOoDzGGFLQMJTC5jQLy5z4KiwTJN4PszDU5kfKhYFSLqZXWuCoYHKKav1f8/Fr+XX1yB7k85ZJzQP974BOwWgPgz8R1+jlBf3GIHksaVErykngMe7kDSdRwg64ongpJdNCWO2gglZL7n5hvrKcPg+f9bXV46Fsnez+PFUbXI/Ekq/4Cq7sySfDUYrIBa5uLDZm4mDd9xLsAZhdKEA/azoSO/Ja36VtuWyra8ryzYVftltegLteKjORJC5t9U5XAPBsZ1wWnBr0MX6zIxy0PRvmf+PsO3SuZqjqE5c1VUX5C5P+E/lPk/5RX6e/bLrr9hZXN278Z2f7Anqj2Gy7T/u8R7QctOYGWmROwsb5g3v16oZn9+CoKZzuFA6o/4T8ncDreGFN2kjHDh08IijbY3yfZd0JWJ2MgGeyUy7PGDLv1N3gue/qRCdWS07TxkzFUf1XTej/X39O0/iDX39S0/nWod41fY0och8NsScM0xwhHsbrjPOp8EVsNVYdFlZEHA6q2GK0coapVRqvBoaqFUFXujXl7CBffNV4Kt3hZVBUNCVU9Z1Q5Q1VjuZ+3RD8PcPEdURwqXpgd7uNWbjFXtLAZH84MtWhvfCVc1Vgl+glXVYmqueGqHVCFswx/rFzUhMe7mGvywzUfGh2Fq17BKqlU8b9sykQYezl/CM+f6/OXOTPJe/UzPHj2vxzPjRC+9PcvUdxNFZO3EKE6vzwYXEUuh1+uJAJlrqKdl724u4xm/rYXjkkm/aqLoA2A/CR7b20AytG9gUQMbetyYXd4A74QAftP/siwv0f2vkjDsayDXhCeqnbie+8Y7+VFv3dr+L2H+b1Ho94bY7z3j+j3LqwIvXc/vzc+6r3exns9o98rC78Xy+/Zo947u0y8V4TOB3wcwVQYXp4uXt4pe8dfpJcX6uLlX0ATfAjnopbRepZ3wDe99CZKfcmoYT27jM1TeCC8HKmAZl7B3ldzO8EHdvIxUyChYS6KuyszTKyYTVsuBE88yIdH2n9W0MefgY8bjeCtI3NR4ilKzSQyPDzipUp86Xl4Ka0YFBVk4RHHr/B84ywSr29YJhy1q3aqa37oRWrAOgcHio4/gZIjRS+kBVXLIQ2lgTUoRqJVIQsHpJYonjrgDV1k8n/+AJuox9D2uEkJ5HNTy3Ko1fbgOoTJeIUlALW9eiUxl58O75d7bShMtgZujwdsqcTyoRLlflNWYOzqeFdFOb7r+JGGB6LxaMaaRwze2b/2X+yylvEDr/FkNKAKseCIeGYTz463gmft+Nk28cwqnh3GZ+wV2n+deHZ8KT87gc9a8bMl4lmleHYEn8Xxs4/Fs8Xi2YGIPt8Qz+aKZ+624T4LxbMp4pmrTbjPCeLZaPGsZ7twn4+KZ07x7GjbkEzR/x7xLFk8G9Q+/N4g8SxOPOuKz9ic1/9G8az6e36Wj89a8LMe4tkv/MwntUfL0YstqjqK8+LA/a3TagBHDu4gc4rVZT8u++5By5oK2+u3vHIE5bRc2ziH5xLAUADj1MsygRf5+rfmNBkxBQdhpxuBpwI6ZZdoXeHPCPLjiJ0jmdSeWdCD5v1VeJ6cep0kLy12u6jIfUMiREzXRhttHqWqNdrebQBH8pLzUFVMr63WBv4aqvr36/yiVfsezyp3udE64DkgY91IT4NZ9l7bFi0aD8Uh3vm25MZ5GmIIjVyys0LdWaKbPftlTz00xPwO8oyu2HCLbx00rI9ZJhpux4ZWo+EqatgtjmKwoSXUxpBDtiI7f3ap67FxnNF4GDWeiWkDQJpyYK6LUOtMHZvGG02foaaJbbDf3ZH9wgjWutQN2LiT0XhHO2y8tTX3i5F1Rmu3nFmCx8zpeK5YeD20UOybJ8ahXyXosenoXJll/0UuvABQDBs9sbXLfsylHnfLw37F10a67Tvlwo3w0A3ve37AVupa/yDPIdRaZO+8tqiMFS9jpcGQAYUxB932yC3Vrc6xzSdTddsceNFlX+1W59kW0GSGrsaBTHCrbJN048C8ZEilV+U5Xtv72NBeDG3JQ3uy274D27BTcgTdVuvwTzy+8p7wR5iAk4hnnca+dqIVyGztaWE3SqdnUC0XXmPFfYZHPyRxS0UeulYZD4QMSaknKLlUb4o1E3UKgGSXujgF2byjyJvipEqmdg75DW/KMPFAEQ/eJYeSmSkZot6VySMbjV0micI4LKRjiwpvimnEfMnMImb6QZDBc23ZiqSh+tGecgbMpJVT1CKSIqBYxMVEUWQ/yKJkkjGIxwCrwcEr9iITjWomrY88Jz8TikVFQ/FZRX5Y2rXMBS00bR2Fm5CPgj+uCBneZGBdbxQBJxOWcKAisxYThqp7gSm9toRV92S0csfjtFdjk3cWYzj8IVldYUYVWTnAoLOTBeO+B1CnaXvPAfJiclI4gtOW5AqYU/BHothUN+ggilteuZC32zPFlmTKS9P/ZkFZPd9wP0kcWrQ4yZQ9H0Tw1ZJ7wFgABu8OwgLxohPqrOzcuhIZ5MpO5JLirF6KFBf+ZnpP5H6HXSUN9Q+cj7lwvEsAB9XFtrn0DZzdiSj9T7uwhO3lnUR8i7zySQkNG9jV4ME1znFSUu4x8TcxZ3bU8ziuzzsGtb09aySH/ZTs/ciC3psn8j5hetxsXnacly+ZrN2AahJwXacbtkmxT7FZ5ULzJTZGx5OnJ1p03/o2GDQKLnRAsnwGi6EVRlVXQHUxVj8ZUY0ykmopweoRUa1hZy0fYvWgqOpyqB6C1dd/i0cWKLf22Yd0ulieU5wFPGJOaatKxbeb/uKRBv+tgb/WSpA4SWlFG3EsZ8eIXxkkr6tTbiTrSsnhGJBTNNc3yIyg82P0WLN/EwwVEOJSIspu9ajWldrXhtq3wuewalaoAa2PK899jYdBmHrDCWA5FXTOwRXmRZx6w/L3iKJQxvP3onp30oxkre9De1Gg6zl3LwLzdSr8WSlZrSB/DQ/0+Y6gxAJYsNJEdQ7V2Rdf+hM0c0kntGO4hJJ4lGnSdoXLqrm3tuFbdHo09wF1onoPyrBx3wCVLzppJQ2jLY7M3+kbzIGyG6ramHvLRVusOPGglv018/jeaGpig8EydHKlDcN5aCe/oSeHjCcgy5LSse2b8BvktVFM7uzayoj2kfWfRvYDyA/1dBw8C+vnMNL6LckwfrVTMlQc4gqZK2A50/ag9e9rtEy/DZsfYR8N3N+GCDiIJNmV8HhcLYrm97ejD0PlAKy8v5bizn9nLUovPUNtrGk17HjYBdvczC+24pNPqg9ugvouXB9HHXL9UawP1qB9TfP/h+0HCcuCsvD3PKpdv4j1i/1Y2PkVGpWe+Z0Im++GC3h0zct49aLQb0a8m6CR1iqyFlFGwdqzX0XUIn4Nx9rfw7XkO2jpg7UVkbWIoht/g9qvv0KkA2ps+f43lIRKDaQrabWWkA3+KqJMSFhiXSt7MRkKCE/HC0mz+PnfMPMPzobt40Qyc2/LxACSJyVBjwaXe4kexYYJkveZC+TBH0Fo89bTW7lN34oJvZW3UU+H11ho3IBRtI4fcQMi5EaK8w1vG0GbshFdQM+Tnqv4F5O4UGOp3S2ZqpEDzidSPcI2EiQQ4UCgLmL2uIgZ4SJW04mFyksWk4ihqLORWQq2mFG0aCi3IS39aF0wSAIVJ8zZByDjZ56AU/RihgbBI7Qq2F2XvBLkJ1ONM1uy5jn9Xnryw88//fSTIn9VopRo16JLGtDsxMFF3l7RHMuXUA+z69UgmCmxqKoPI3y2X/gPkrdSZa4yvvjvOTk5JQ1XKyV116RU0tEInpBWyu7Sqvn8emsjEWiWvSxLHrZDv7MGXRM3gEA36XiWukO/CcpZ6gEU8wut8FuvxwVX14KgKBfuhd/6RqxA92KMbkhjMqb1+yr0Wy1TLeM3AAAmcR3SLnWNankE6+KgrlVVK2gyHIqy+gUdTw76PZ/A7a9fBoNa/RH4SN/TIZSlPR77E1ROwbDbeqshULf9+y5kJmv1lPPR9cOofoN+5BzsQ0nBfoQnkBiyZe+hWA7zlcoBlgR0gYCaTS3KKMwdOvpRdNS3Zqdk0idBL9qcL2CL07V//4eM7u4iRCh0j18I9Xp+Nb22TLyW8BW+dgj7auDEg1BpeQ0rP20yg8BOHOl6aqwEXrSKfdUe+BIXHeRCvehMJDmitRi5Ab454Qy7R6TrL55FfnZY33AWHTH01fAHZ4dGzOWom4v5hVRzQxtHyXxclBKu55yhzdcfwC4BXkbqH+HAUDzWq+iDlhd34KFWQnxRhAEZ5Xy/FVZj1heGCZl9qwfNnw57vvRLNEU/uI6CKgMJv85o8qr2UNPXJuNrBfTaDcZr7zV7Lanpaw/ha8Nx6UAiTDXJ3udJcECfH+8CBPPVZOLBQKeajGTQlPrFotls9XY2kp85IebKeoEd9CSxpYNLCVEDA33CDUazfRk2Gb1OljrA+9UnyJn4XtX8pRKYyWwukHB4ujFwgMFkGj1apUoQ3j/HXsjX+Sge17I0u0bSDi9Af2focuoJAriPcWajDyD/fv4D34nc7uoJl/qbEujzpcM/0AbUwqw99jm+cjgPnaO1NZ8BzC46iAe7J/CQoli3nAnzoTc/b8KHPt2G6/15Ez5UjLVPft6ED5Vi7QOfN+FDH2PtXZ834UNDsTblc4MP3bztf+ZDvsn1TGV8bwNH0J+oF+cfqMSP1NNPk0ksMOgfU+ADyTjZsgPCBqZvOQ4sBC0OBhYAYgdOCfqpj22gQxs99RRhXGsD4w5+RvEPeiLUL2vJxpEWPjaOfP8pG07mhw94+p/x8rN3xLMpprAxZr94No2e5SXJS4ZYixj79KUniU8JJJT0BScNM2eg/zfivWGiz5n4TBi+lnv4WW/xbMJJdOruCxr9BX3sSZzTCX3USbSrcQ63kySBrTAJCYzlr3afczDz5J5+NmZqfT4LtdOSPkOxqCpUAVKbFd/asQAtqiY6R763Ut1aVco4Nf8zFpxTtSWfhrDLt/AiUkTKqRWhjes/HqN5X8Y/sqhFhH/vyBYh/97RLdgZcnIL9mHMbxHy8p3+GTtEgmrZmjTqCvjGKO0Zrk4U1WgiGoVVeKSFUohKtk7DoIA2YnuJfE+Jr9ihli/lOMN7qrW3FtCudQE+DbTOdB3mQh9koiwhaDVEapmKcXxADDHPSf5SsubnxoNeTTo4kBJfYUsiSFfDpi1HiUMzf8Ynr51DY6vQij+lOkW+d0eIpv32WZgeW2EUNhiFYojXsLzOUiBO8ldecoBUas8Sk0DSUYkiBdqUWRAuXnWSSLyXHpAUK30aJllPtcG17L9yC54i1ACZgbIjMDSIab2m/9wO1+q0olajU1mJHqOuV0oOmBXpjFCuI/Tds/Iz8eh0nyOn31WKzs0nc+Rn1gbMAXammLTTik9KsBJLZio57OW5t6ilAUXKkZ+O+xfVOe2nX7rKUxwDNe5/hZpNbUNlo5OJlS1y5KnFKC2pLEVR0DusgYKAqGiBT5hvZtAsb0ZPvYVsEfHtxsVYKxYDvewwafqwgO02dJib0IKNS6+Q7fxE5Pnkh6VR54f+D1n+7yqQdjH1ifFtH7EO8LsDCHgmEOLVmeoZWFPJ8O4GCa9/3mbJlDX+GNqR0AqZmYZOorm3sBRiMwuuPNlgz+iRi08miL/pBruOZw+oUZiQ4mz+Sjovk333EftYmcSnSw4EVjZqAd+RC3uTiaX/mUoKAkvPTDsUGIajyFZLkKg6A+b0VRgbFWXPUNe+VXvBPWZ91vh1OOjhfnO7e/wz2+EiOlPW2utkd51Tdh/wlEgO+9q8za4xq2FQ45z+XJvNrVYpwo6njNfw7aq7ZvstfyqRTJFJNVbYsvEIy2sbwbmgTPAO1mhpHxOle8VFCkP/OypRqTbfpPjn3ETAn1KJUYEz/06PE7rD4/xltBB5bsWzjBYhd3ZacdW1OX8QPwJv7t8EguiSOXSkiNk6/4xrbCF/G/uOvD3kfuIOfEyDQsEi0ZQrKzDBVAS5RO0J2vfdsnerlYWNDG3YfBKVRkLHTrUBNAlcg2rFE2cjjMSOMP2Gv+dwIEsij8Wt8xmuriK4cqtHgNZ/NV+cS4fHi36DCLjooDiBEl2jZyFRTb8gmX5BMv2CZBasRgor4r+c/r6bQamtSjDiF5e/L87N3moMMaLF5NqOIYlZH/AIdugvNJIf8ig8WWLbt/q7Yzn+4M2MEeTmQXGSjLtIDkiPwedynOpM21+xCMABT0ZKbKwlj360NYEkCm3m2DBeHX7Ms41C94mbP2Tf2fug8xovdSAJ2upPuHFjaMNl30PoVCw2Xfatb0XtcShdgQpg7kH2xpXkWTMx6+sKQnQg6FNb4kIJUuK3/OdnEMdL9rUg6nHYGrag+s1FwDrc9mK58Ml25Lc9AZX7a1qFQGIqCuOpCBeJ8HSU1nG+8Hpe0ho/9BnN1EvGWhA/AEkmOFXAQgolcWJC8gbYL6RU7pQzwwP9UrVv3uMOZrlaURBglr1x4i9+fA+xF4kCpZgc3ZL9ExAgQ6d+acEfMG6fTv208fOZJibSKZ9vRJC5doY2/12U8qPhiUWoBcS+F9p2iE3dYXgMAEj8pQwNUOXI6geQeN1//k8SG7EVOzed9E/HCg2f+WpycziyssytapnqeZCwol110GCyA4EMejah7419HneR5FT3ZUqHN9c5pNVLUY1w2Fc75Xv3OQouTStbJ00tR2kuSz0P308S349XLERmSd7API/kjIIagtMaRIle/motea/oj4L+rpXME5GmsjfOgokJ2sjeWExaru5BY+O4/4b4/3xfIP70lgbi3zOPkCQbt9YKI5sOOu5bjtpG95gzDnV71viTRAW70H71Rx05RLrnwL9AXG8aHqZusF2xU6f5Lb1WSCwfrWTOdfQytNLyPmLK1M/9Pc8CTtLhneBXu99hujJLnKWfBLry3LtGPiF//4Prw6PwvhBs6o8I9MtJtlF/W3W9xOlWnGqdI/CMdB0ZwEr2WdU50mwHiW8SOo0AwEhFwnnEqa6Q5jjwb12oOTy3Gp4k7ti+j0G3LnSvUkvR+angALbLVFe8gX6kLjUT8bIdflpNZhJa7fL40N1Dcvh96JlBUud2dog5vA4bLrgSvd21jHk50Nuyt4048QZB95jmDnhH+Bnor5LNxWtDRzZCxJiaYHBIIO42Vg8HBYNXm+QZJ84zR07FMw4F8wVOP4hV8o98DqaWUCoGZesBirQeUorgmaqvOs8CciQF1Pa+G0Kt6y6Js87qyWQZccIjjsJHYu6fY1tKbM9L8R1sToj12vCkHHQm52YAdRDS+7fA5RiAnv6e3ZhGwcBKzhuLmFk14n/rizvB6xQIL49cBi8bES/lVz5owVgd8x7TmXGa9V0xFxvPZfI8oYV4kcbg7lS10259S+zHA6gOiKgHzGfzttgPzqyUrb3wNhs+sskGdSfmMfN2yo5hLanyOYmI1APvisjbq8h7cnJbeUlG24Gtcs0Dk/Li5SXDJPSjG5iUew7qqoVIrlXPhbYl+1rLXsxYoVsxvvm/yw/9P6gg+aGFIT8U1Rjyg9uu5e3Rl9dSSMi6tC0kk8MCPEdT6J9RwdK3r/Acw5BiFfR2rhBT9evJ+MYgDOA9tALN+z0WVXUOnze9Kdat8WIUHE+aa8AxJqDWfnnTIHZzSpHSgbK93rslr7Nn3ylPXZzsawnkclX8DdDh8Hk0uA3lkkn/ED6PA0+rMYa+ArZJ7wwzAswmy6rT3z//e8CqeBEX9SSPJ69bWJaIQYCo1aS3eES/Of38qn5bHcWATcA1wBhgFBtHwW6QKgZvBHGdyDXlzTpkVYA4AK1FlEI7rQa4HTb6C09UVr+UWN5NpV62CHaqDX9LMOL76zjGusnzG9+iSK0JBEHYrpLClGrqeeUX0FjqQOBQ10gsT2cG7g0TP0WdSa5yxkksrEvMHKKGM2OKiPJ9HDO7OQWMD/vSWUZjx5KGUZ/qZsVTKlGOEuypCGlglrpJUUG7TLCuQVeL1oIKKp58ooL+fCKCBpAg8ahiidlKAxYHxBIMPH8lO5557yXxbqwtXS8mS1+uLYP9A9RaRC0lrcYtpg7ToL3SDv4LV48LrlbtUO4cYctgqySpmuJD2tsAAE48bM9E/NtTQxxxAuWexkgDYGqyt7Km+Xai1ARbqr38L94Pgv8nMU6ruKolzP6O1dFievcmaIY5MaNhNR5Goo+pwx5QkdVfPh0M5iZr6+aQHixYP8owxPrRN1xgg/dmNHt8MAcnArIWguWEkCAQEg1AIKyQKKPkXsTwYgy9iPW2QB/D8LhOwCxz3XYnnpYvJM4uv1bqUMscJQctjpQyeGpzBrKD+NXpa7H7kgN3Kf4s+Ntwl+fA3W5pl6JWKiWaRSlo2ItvT787lg5EcvEMdLJ+WyOpGn3LpJCsiofjMOZ+RcRfYhg2cNuqWms/vy6wE89J5hsmK0SjIXMEduLZcbr+I/Af7f3XeSsoHXUT4qGvvCA4WOQX2mlPvi7o0e0kHIqvID0HstwoPrLTpa6G4ldzOJLN2weQbXA592VSBHkAci5NlEya+qag5S3q/3dabnvdoOWVAAB6NWZ+3qvdCR/U22D+eDQFliB1K15mNjL+k/oiriTKgRn9FX772bOE4DwHFZQYofAIfPNbCr8B/QawZFQMiWMjY4RqEyMYO6+MNuYN1mUO4iZ6bwZgreEvSLK31zk8MbR/g+i9kOKyXeoJRf0drV5opctUj6oXqlp4XjJF2h1QTIY5ffG6OHsEHOlcgl2cyFQvUgCbiAelizmEatwvpCV5McWvwK09xdG4NftsFG4RFqCmMF94PVj1s9Xsr06o8z0AIedpaQvIq/9J0JTJbrVCXlLqTqlVUirIpUKxVyjysDpSMoCIKlv3qfUUXDa+mCSTrZpiwR/eLcvYZchZ6pZ2gOhtM8szMH9Blr1c6Qri1xb045IIMRAXEGNcKeuy7JsnjoDWuXc/m+UBzJIQvdTp6EJD2GLYWoA2HgetVK9vQD72L3zuVEegxSK6UQU2+qUBj1cQ19Y38EkboecxizIIEfLZlfBmblUBM8+2b+D8z8B2xhJ1GYYZp3GJ7qQfcbk7FHVnmKgQMYle2M8BrQA15rwKHSXUCFWtRGvhDvSrMJLxAuXRRzQIe2pMlD3V8RBbRCkI5IG0E5RctOD4OMzpwrbT4a9FBZODvKndTlUJizCF4JgdDnW1W4QEYfLKWH+ft2FAsWsQfnPb+du+tZKOS3zDEMLHbyVDid/yDtSm7XYHBsY75CWvIJ9xBb5CzoT53PKXCjUHA0yj7EsufxdgJfatE2+DAdyAA/C/RhYjT0MwNw6ewjMZWCIS6bEcL3p2NqgJ/GTSekXdARt18kfJRNzV4Z8zI5+iEStZkVDU7Y6Cfcx4j1pz5Ge8dyK3NuyRUPPL2hxFnro2f4qtDSDFHHw5kD1YkZdpd6FfDhBkoPTmzi71/bBW4fDPQA9w5LV7mIfPgxHoCUEjYXLB6nFNcyXxfKs9mSYYfEvFXiYX7ud3J8C7yKBI7iFKQyG6GDqWPdhvTs4BCBvFRMcpMvrk4Fm439L6PxLygpGa5VViA51/RHt0hEpZ47Q9KOW1rvb8wyTRfYnQSIJGQ/0g+lO+2eUB5gi/hfKnKii9j3iFqcreqjISu+G9khXivfb4nicg6HwwbDfKRc33qFYX4Hd36wfhGX97BDFyrnB4CDAktjVU8qi+/BymojsxVrN/7WMIB+nAwvvCMPQ3MQOdS55a4kKvwwySXZy2OLrIDSNuk9FnMFWkKT2LQW5JiromR97mRvvKCUp75VKPZ6X87LKvccvDtKyU41UdhLy6fKYQjPOecqv73eoxnMZokldnC46Y+xCA9PfkqgfYD7syWjvPy5P3vFs9jFaGZLd/ZiwClsuuT/SjVwhUxnFyUnUt3eaDuJ5EdzgKuplbziYjdY8CEw+1Z2dEgLrwW4p/TmeSMe3rUYPU2eEesxyoJZgoZDT04Uopie4mqoe7A844yeim6nsYk94ZV3U25fexdaSDmB2RiVYwuFy9gHbypaSHn0PWVCzyU6wVyVEqw4lXzsKmi9MGcotS13guxMi+elZcXlqGOzqXHSyWsisFH8MY3ojoygktEsnZYoVtuEQtMzN5NHTA659rEk/d/FQRL46GR+TZCJJPBjYv5ubpojll8YHqZHptLntp5uOGencXzSPiW+S1dcenb5RRdqLpv3RB9vOj05ax7C4iR9V3pZSijkwjITW/4BpqUrwq1KBCCZjvwFisDGHtW0tM7EfjB+jRKib1FT4BmSVGG+1xPPYp0WIVC1oVlOtMpn14GomcO8ZlLwegrabckfR7cDXCyGQ8Turi3Z3bMSuQ2wIl2rQtmAe19qwrZVvIEkh2wLQgWQLdao02aibuDXMSlwcVnVtiDOetGie6+C2kxAeE3yhlYBTpqhZGxgct7mUEvTm2cZRObVPt/Qc/eWd1kjJ+JjXMGCwja4xVag/AHzMsR3ucYp2J7Qu833OTxKaSfhGYyzaj/JBCBBs6EquHUHUoDKkiPxQFRJgOYirAfRGH1ljOfc+RUG3zB1V/T8n9LySR9FZpYq1wdG1liXY1zOEpil3DBfCCTLmIz+g//7uIyODMDaMlTtKAf7UfVDRXCHu5E5h1ZVQe8daq0C97kdmuTPaOorjsNVVbXcC7DT6rbXmZhEZ8WT92ESWkEbYkl1qH7B+7zkqpy8KYoZm0TG51X1pNVmCUDTRN4F456mKHKZt8p0sw6Iz/zoeZFcwWJrCi8VeHV9mtzsX1LM9HiU5CwRangkYwWCttiWTyJ4pzh+Uzmp5nYUuQK28pEudZADboPVhIO8/QwacOC0RKkaUiEUmxSC2yViTQqOQUIzs4xYiR/2RGyOq6iNTBNnk3Rx8HjSQC/zH9hYHjapLXQq+X0QWokQ/yM+j4tpyPl0xG/iSkdSOVkoMtKDMf8Fj8mwg0swzNBXQCWGSYsuH3IvFbuBkruHoLTKEjXsRqjRZPC9m/vSRNk0swPog34uZU9C6HCqsU7t64Qxt+9ghVA3Fnw+hC2y8mpqY7RB7i0UhS5wqhnXHF4vwugqP/LYalRJjZKFui/HqxF+Yt+xQM+gvMwLg1N4Kl02bN9L+JxeEB520tlM0nlc1apm8LUJxqYARXtcj0v49Plc3H6MFulLO5y9dKXQDqS6BbT7VkLZW9OyVa5XskIaCmKyon30GffUxKUDTHdrcwvGTjQSMOqzVvi1oi+76OoeOW+Xzc8nQcr102WdBRO6TlTiGv7nQyTL7VHvlcri1V9hTebKJzjcmUrXF2e/7KBEWtM/ZdUXPhtd7i/EYVzu8RO8vBDniPnhLolIYaA22U37LiW1xXMrLJvv8Q5lh2fBux1iWt6FzFkb/qLa4404rDgN32fZM6YU4J5AcINPZS2fMGnRW1/Rf04C9AfQLPCyazhLNMymfTSRE5lVcCaqN7H+O1Q50zDBHbpc6sQMSmGXJhPnzqoFz4eXcxDUqCnIyGnERebTw3cnhOS+j3nSph6MJrxY5WJZFQTml/R1N6XNw7v9g7P+8dbmgqnrggTMuewCU0eDBc6ivb0fxDKw3UarLSm801imcFbZy4ClRsJkYmeDiaGB68gg8GABbKnnfRYm3500eSiWx5BT35ws3peOa+cibxXZTgRqMsl669/C4rPen4ydGU/AfmKXsfakEej8ZmxyIGSnTkhvHIkhgZwZF9Js+o8GULD7aIxzQYj+KWjMCMkLB+njMSA+xrxdbSIvYMlb3fAcOEvUuWZB/lATRg1zdD0BlJgNVk/AxtaeHeRmFZDH95YlsmxsUsLljl6avaGyvl0axpW4yunBiAQRgEqnDvmWJybhRhNyq9UUfEizfq27G7Z51+oZFsMjyM0D54O7WPCAaBWQH6nIrjgSYyxqWs5VHzCq2VPVJXPtZKh8mNvOG/r8w7vYyV8b4YyrcKdAdjgEX+VOgaKe7oLPUoMspfTJzziBQ6AKy5guAlCUaxw2QQDs7Ethbz1tg3/MC6/5ASJaVKiR2FS+EVSd/gA/ISFNbQglnVN2c2qNOUSpNY8b1eEjzJGvzPlsAy9uQbwas9CMNrvgpheO4aOrJEK2Ripno4C00mIxD1ToUlU+G8gBoWCfm8dlCdJNyaRhvgQZgkzyk1kMkJGIacHohhr1KHuhmIrKwubccI6U24FiGfJU5nEYOMW63IUvdhbBSfRfcd/hXpdqn5PwqKdDApRDwXM7DbKybdTTd6uNTVmOMUtB+KjCDlxvCXnyy57UcndQaKpZ4khTalQcspYPVlv5uztJIitQfNlOly4eEEtsHNDTG6lAq56IkEDMeqlQOP4g8pyMBUwdYtZt2UwPPic13gVwwKxp5i+mOYwPBbAB4+FOOI1F/sxR+YjOGuubi8p0NOL0otWw4NE3wIQpAfQHsAFPQwZEqPd+TIX5XhqZzh723fKHvmd4wIR5Mzgfb/Ggos84+1ZYNAgLmhqtKAzsHy0MkuLI4rX9gbN4j147RCuHSgtHvaGf7rwFFiGSyQAzzckSBszr8jeEhXNHPbj078kJdRbcS8wtku9Rc33uszClnZBSXQp0VVl/B5be+pAmS/IeuFDtDtVhvRF+OfBUIfVdS9yH/QF4DmIXv3dDCZaPhqKUXCgMaXFbC11KZO46n4+gf5NDwJXnSnNMBHY8Q56PKXxPfOtG/yPcn4nuzd1h6Dd20teSWwe/wMmjDOUCToWOZGIM5ezEq56BaI45b2GQ5Aej85ihJ/EhclMngWXx9BXJF1Ar05chXHzLF4AeynSOAjUVpDVEOTgAW5L9K3EB/ipNZhduT9Zz0f5nJqi7hfreLdwsmtDCjv7cTAwymITdvdAcVqYCjONz3thNvf9/svJaFvqhcESUIFOYkOaX5yhDD1xusNTLWXTboHNgUQlhOXUtpi7SUBYJt68KLwGN8oVXwnMuQ3yjOSzsi+hi4iUy2lMCsDicHqtl+a+LabJqkew3EkptWg/J0kWPloROR0gk39lzqRT8RvkWDU/nwSSshJwgME3zuqFkETxIt3BDhb/WTOGihkuQwXYtB7lHnW9pSJnZyF+CN7phPBIhEITRLDNhP/dtm3TXpGUTdzaHsgYcRf8LjXnXLaUKnchkqVM4UOugHvUE2gzgDqTmorXxS6FObjdaWU51pcoEftZucScmVTJVCLI+yHq8Yi0vxrGtmQunwRRj7vYEQ+FaVqvyEbjEKzq5C7/YbcjZgcITG5BeWjkAvgL/4H4MXNLv+MIifzb0UJ9GuppNQr9m2KPLhEP34+6j4d+yMgSS1r5MPD0RzXNOxzCThCclV8zmzt7hcEvv0r0t9qtPC3+vEFw9/quUYRzwKg9RnqcsKfwdiq3PSIDxxZQBpdHPRf9fwV9LnHXgjpcwfD+U215c+H9LEJrI/Jvpno68WqanPVLEIlE55c2gzYTv0W7PKNYrd9IcE6qBJJlbJvfQvhG3/r9aSO9CW+mQ18816Svb013VhwYQl+D/BhlBTyjfBKBPfRaNdJxB2jbGiCJKRtCX3q9dJepQCAyWFh7XxnVg6Smkhqfc83k9TWxgqxxhB1Ze8QYXdnYkL8Q+9lXB9YFt2lBz2lM7w1su9b4vtAxPDg0/cJGlgCQ2PRJ4qStxVuxl7t7LkLQ85nu5RJnlPsBUXrW3wKtIBIYO4T8qwPRcUiHtMkW3g3yR6jFUz+v5piegt2OcDLprDCO2milq8+jVCGXkskkNrwaQQj+zjGyHsa1odKY8L6UHtBDAaMsCmyZwIDpfppmO7wYlEMN1BdRR5aopbmFKw35SsDYDHlTGBbB1ApwjuxSCvyPoRaEQVtu1TvdlaNnGjPxYJQjY6g45WHFW36SLWJK1Bfl/LZimjKcw4PmCnsko76AIxQG6e7hAaXouvBDFI5S5ay2DmYrHLVLLzJS4pV1t6j197yHEW3uYXAHLH8xoaMXxzaBtLRIrbCTjL5TDKLgYjtDpg7g9rmVouRhw0q6ojR+6sxR6R9Mc1E9iwRmZXSo3RbVGX1dmcEnbB0/eQydB5zA9JavR5N5/tF0flPw3T+nUg6P+uKdP65CDr/1Igr0fmpzxKdj6DX0fR+Y56g9w/83+j9p88T3N7wcQS9f+yS0HLDJB79Kv2UToDYgGFcYcqvZ5wLBv8H+t7jUnP6XhpN3//+UZi+P5kr6Pt7l6Pvv+ca9H3a/4W+t/goRN/b5F6BvhfmRtD3DiH6vntSiL7nG/R93v+Rvn8G26gPJiWXrDG5oCZ4MADFCQJHMib78P67DZ/2G0pDYhE7I4SEupRqhU48VdZd9MfgdYT3P9B6PWNrMK5lnZtMXrFouElZ61Z3hjZorUseclax105qRWrV3FMiZKgPkjWU5FhlXnsqHL+KFHUfeQJPr+8ojPN0r8wWXO4ouz20pHAB2WfXYP4jNZYgw4wKD6DSo7iVsnkhG1gkjRiXwbMMnifMYKvjWLtcIFyOvH9B6diOCXo9268KmRfcqI1ltBZkMNLmlRTKeCEGFDKAkp8vnQ40oRTpacX6yeOhezqc/jnCND7FZgXFU1HXZGLQ+KzTRNiETupnbdSF/k+GUpzPFne8cNC+Q/b0Ps3JbfmhH831bvt+2dPxtDDUEv1Yr9h3Af3YClRX9tRV49aXCnu7mw/vMNGzujlsfE/onI2+DKheCWqCN4Mlar0nojVekBG2wmsz/inIyLXthQn+bx3ZBL/9jwwgGOFOyx+DALKEAVa/LQrfDfjVf61jdswKjHdhnKEF9g7vgBQyTOE39A/hlSz/m5gTLZ/PrIBt5gl9AwgvQPjfWzGB7f2AgfkG15J9nnash8eTmrEZIV6dKfTdjUDvOvH2Wwm+dip4/lftttdM7Ji2xVVbgwBdjgpzLeBACVF5cytyhO9BbvReLLkC90jKZt0VMLdD8MuQC//alSOYvNutIZbwk5UjAgMJhfeEjknQbqEJskE0X53DDicCMrXCCbBRxWxvDQhKhiYTJM+VwqI4AWnCaCSMq58RW2imLcS81N4U3B8JXqnawBzNb+VFSkff+1/b0EhFovM8dBZZC1KOqkgggx6RC4+1F7v7fXtaY5f65uXI7OAIMvv+uxJQ40ug/wGxba3Nf/oKpLbLMyFS25CFBqOtel6t0LdAxaMc16Sdg7JtGJEi1OOwWqzYqyb1NGwIkzoKnbFC9gRiRCp+cjB/XqbhWd+NENO8LVmjmUDJ3fH8CKMzMeVHdD5Z0P/ejZDkzJgd7keRbs9pGyl7n6C5k+uh38dMcBQxwVglZadggoo/Yfk8yTB970dYY9M3KN9fCOI3wSAl/kKUQVjWE6dZoAeDzFdmyHz2UULmK3WxxzedcHnvI5EPbTyGOjCzkgU/I40NllH2IzvVR+gxJKFZiC/5QWREinR3u0jb3U4jUkz/4QTwex5chICUj9mf7WOxQ6T2fh+ejPiK83IINElEUuwbJ91OuJCbSosGTBuX4tosdb8rBXBrnVsets4NKFaI2ayj/FtYXqkBXND/2Ujyhkn/T0S+ZkqrxAcr9q6T/BHA2OEd4vkij4zW8SkhV+DNzU0BcvpTwq9OHxo09H6A+U/CAB+a11C620rvJNqF4DNkpqUU8mP5iAaAsUr2TL7EJB7RW8/l+wYjBjr+bRqoLPx/n2Skmdt0jAeeFEijvxCMnL84B24FVFuKi6iw7wDIKwO+pA87LmxMYWR6Cj2l8BBVXQdkqcpFAqhBHcOCKNEqre5JZBlRRChsH8VdDnMTbaAYpYx3kmUx9dmN/i6vP2HcS/YTnlne8n+Rn/7+j2Cw6g23X4zPTxmMrOinOVrffYn5ZAh99NKLfNDKnPecOKft+IQgRlE2ukf+YcR0Tv49rRiDHP19278lUT5zWdnhVoNA268WHjyG7AKUSB90TMS651zuUqXI+7KNqAzAUfn7OQ8gjkIJkVva5rYX5/1O3dBpFnxiDSGsgXLf6fwVIN0hWuD0qwiKmchkjlHq9YIIMC3gU0zokTLjXYySs4NvSqZM9bgLL0tB+p0MRPrCuMsS6VPaxPEGkUZa71ZPZaqHqWO94kLEEYpBaww7UEhmYnFhQuhUkWUH9I39DO92rt0RknpUDyUFyd8Xmiw58Vid/niUqbzPxeKUDkbJ+aSFeW2HouZ39ZuESa2168ddgfO8Oy5CyD+C4wC2u1YcemaIQ2bdcZ6SVWS/i+k79kSKrSA64hVhQkiEESbiyYT3tiMRxgfZuwPzaM3qdYTvw1hkpDeIP9LEJQQEsmSt4e+XN0OE9V9cY+w52hzR2Z2iUbq1Hw7z8ej/tA2kcxvSrtAx9M4HxMq7hbsuCq6LjMM1jaSS1JA5oJ2QgWJk70UhjKWj9BIvvISsEksxdZHn+osi3AYMbwD9NfrubJLA7Cwqy57fWkawHzwZGIkJXO6ro41bJoVoPvq2+lspgU75irQlCznpFMKGcnfKRmC7sudjPEENdIJOzsie8THiFBiYJh7oo0R9BiTqbSRR341PU0rd+DkdQyXQllCpEJ/07Kjj+L90PSUmnB9NJbsaHp/TPX9znmCT12gkiOlKwHIr5ljEy/78GXG1lZ+bzWSpQnuIpcgnmfQ7DgSDTYxr1TGGcT5kXGvVIWSHY+2bFiB8qJxryzY2U1+1H4BeiKd57WC77mFobBkXcqFA30h94smoVWcr3FKzkeIP1+AnQEX9xn2kDkYKiJUAd68JAdEzjpZ7P7ILXP2WtNzmDqQaPEDP9oFsTEeSa2GlS6jngTEi8nif7MnZhyvN1pGtsuch/B6Igj1iIu7jCRs6G2NQRrsYtmqiE81CcRol1ER0VNCvrUJkxBD3cqU3a9Ru6Yhi57zcsufYUU5Nloh3NNKp2LErnQJs3Gec00YetgxrG7aiijMV/Zr9IqnPTWZBf8MaH7pQqEURtCufZQnZ+1JNFP3622vN6fPDY65An7eMCZGyU0SigT7rfSj7UBM6mXtbxDcuvCpoZMyYK9DI58dE0Mjfq0JgSur06YZoYtNUrRbOFZMNBRvzGrqj7W4hgH3/9zBpbdINLH6oWckecdzzCfMBl/r+ZRQR2dtlT9RidniVjUrttMTHhOh3/vfLmJRefswwKW37HWPhIscR9g84uxcwYvdeHPCKyxppTMIRB0Ob0YWRjDQ//hYMupAWbW/g1HGbGsI4KntLoOTCDAesO/7cmiITUSxCU8JHDZRRhUIr9FXCHJBknOGj8129JXymD2Xf+7GGjdLqtk/BnAXftaQkpr6qFtF+PT+Mpb1R12NljuB7IkjDa3uaAs8P50sh7VQsq/Cd9trGUosN0AIK4yKfoASvLRlD0521l71XV70SYWf8Mkak7AR4RfxLItcBw9T4f/Qf0JfDlvhnJ3Gspfc5vCMZU21wcICQPKRSZUARMtCJbRX7IjpM8BzbTUQiHlNu7Nfv2k1WG3FWejlXH6eB6FbYUq38byGj4DcnhVGwT0zIX/J/EmpfA7jTc5EWBzpRWiT9pXq0CLqZvCW6xBllc9pEol+1sEdnuwJ/ktBOh/Tqqt+EXyQosy61jl0idW1bBMGHNZY9mWaDLtnXy4X3HA0b41FnUd3RPJvs7wBPiewfpe/G25kj5KXIxCD6P+mKRPMbNKMEjP3wswMMDEn/67bI3XqpmnfL8OAM0ZWIDXPb5/OG/el05IYNxlfRc0M/fhFtT9HEeBFsp3bNX0N7tM7YI8xNeDlnyYXNnCXPjYbdefUkRRnlcN6EH6yUFQGRQ+IbctPL8dhE5JKBwdM2BZzWFspmDaHYJEUxinsEcCXpw34zrmWRaFMN8x+ad3AjEt3sE0+WPQ8aDPXY31lGS3SrW9Jq9H67eGXnCmeMdD3mV2PvedfP8EZQIhlitx2ORLHbWEwTd8NJIy8UPjiDVpQN8FIrkopansQX9qGbIzLxSkxvTKz+5AmyPVctwOiR3plo/CWa7ytGtCEPb1nhRDslrlqOR1Xs1fB+OeXrcVI3he0slB1Y9vxwnumqsY64467Ag7GKfZMiD91EqfPeECePk7k3qQQNHbjMJRHe4Gi3VUvw+IX0KYf8vZe8A4El4vUC16HalSNGALSvdhfIMiidqDC3e0sy8b7iGbOdbIyLFGeFjMsyrRFjRrItFjRRyW6dC2n4+pLtpOcPD8R9x+cem2VP2TnmAsvPRXAB3/dVQpUMfTXKY/YyArX+Z7zk2+J8UcIkp+Ie2BxgOgibjh9CYTBNqLff0u1FumshRPFznIKWCypOeUaIgp97hCn4u/WEAk8zw3qlXgwVAF8vrI9E5lYHDdKL1EMqRfcYum+FUFb26ijvCqw+xv6J9qW4UhN/izgIZFLjDpGaYYciLMsbj/DXR7vVpZeTAHxZFr5TPDmibqGZjyJYNSuqrYs6Fe5obnoy+eRfEI041sFQy9LWZaGW9xO+uzKkoaE2Nn5FWEsDIKo9QsqZ1IDQzDBSCUKBG81qs+BtV8pW4ryugHmAMmjGy5JJnvFsnQhd4JfVzfrYurAijMzbKpyPrP5UdPv62izMLm51ZROF2He3WawAfSaSiOvt6gTZU40DXHFKW/joAZbDCHE3j8U4EhL4ShR5yFpK7ywPLscvZiBrmCwOdF32Gtlz1hRpmz/M4RolgPmeegnXgA6E5KHklk9qtlSHWUQYZX3r0ObsTsFDJqgtB0aYwU+kLcCYJlph9ShXBLxMQtE6uaiQcAlt6bfdHhZP4BPl4kIIca5D6QHv+vP/xYReMFKY0C+ZhAk9tyUbsDaxchzLR2+gCyOFITp0WTKTA3QGKQyuovx9MVIaIDNAbEKURpCZSCd3fTeZPx7gUFq2F0HHcx6K6JjtRjnoie7cjISudictVSn0udalvnJ50uUOky5BId1/oJM3bgHeeeTBEO+sNA496xr/V965FJZdnxs+I8U13XaKYTgD0wClnMZMgcePNBW6wkYlFr4MocsQwnT/Fsp/bEjIk6DTqs+VCOFxR/jwWkhNIWESCawhuxsS5Whxsi1caUnJH/9rEyuNNvLB/4eYHTL2fnAh5ENFw6u7gg+VcJk6+QsrV/niYDFZsdtlz50XovSaO7yGXpPxgNBrely4jF7zzQOGXnMJw3T9fRPyMFmW1tp4a3BtxFsjxVvzHjTeurY26rNlHpD13bYkJ2mla0Y0zVJhfHbAA0YcPJIhAL4kSrAaMiSgESFkhk43JEUl0C9ekWrc9uDEHPJtfcUUQcrpGCE5SoeO0PtsZ6MG2g0TPYoB+dO13c9g4CSTQ2NbYinjaz2dgZ+edIOwWkx6Rdmsu2GPetN5UthmkYv0F20WdbLn+zP4agP3l1KaVhzyoQXJOln2LMAsr+hLpQ8J8v2mkZDUbsT/KyQ5dvM1yuwCjicrkZBE2qoBTlkYEwXgpr8P2BK2n6w8zWZxlsUvhpxBDXOKYUQxjtnzmvh+ef5SGTb76n02MR8l9RjvvEMLeW80PpKONgDoDGi9OrtJdwu9tiOyj5mVmHFCt+yNuL+egAQvsW8Rym85OSYirFIR1wBnx7DvKKYLoODKFZSBRARTfgrrTMFjEZksXxN14eyWZTDUgdoLoj5J1OPlKTkjGKRm8/W6zEHGF1OoNtGOWEsVasf+pXxrRBEnwMaTaz+nxhbZXaCFEVgJQFyULh6RV5IRxzlT6AlFTiouFocclFvbu65opi2OH2eKaMy24eBNh/zGahGJiSCQAY1liVuNZZ2DvK09jZI8/bGOV4jIXBSKyHyt4xUjMlMj8q+R08eCUERmeUREZrnRRtv6j+YRmSisY0SmcGFT1AoKyqSsBkMqQnkrjNSUvmBuz0zvodxEJeBOpzud1iq1tUrKZlyzuZG3NIkoTcOBhvO2ff0n3sSlPL+g7F3bwYjFFBlNUVofHcNBFWjOVIWnBGZLxS7+ms34uta4IDoKZ4uvjLOJkuEV7S+icM3AUvTswLuii/kmWo7ug4mwRzXFYWL1PvG4WvxFmy3+jRd/k8Tf1JgmUZ+ouUeEewLEjWODtLpUxHjGTxW33Q3o2X4q3g/wURvKq4PKpgjv9Nq8JnFpBN5DjUam1/BU120bGArvTPihL0te+SLKE/9qW+/FQ8LZTv9iYbTh+M5a7cZ7mSG0xRNBBZ1K6DzQc0/UeWCTGMbJtAuL6S+IFlMM0eKR+4Djv0P3CbK8yuGHNTC7v7wkmYzoQHyafJlIQiOfa6TVwvidFNG+LqLeCFGMCk502hTjB1n+kP4g7Q2HGrZGvj7FNtIlVbj8qxDDXf4ZRHsDn2EpK/AV09+Ef05BSvIFn3dUyIV6jOH97rkUBAwHfTZVwNJs3G7KflBhGA3k14sdvUpAPZm1nTrYJs8pdiatxdjB7BYMF/HOwMNBGMvAtGIYbz9c6OVBunvzkHG5UFWb0H2ixZK9IneyMr6aE1MkxNDw5tzCgljCWVAhs/zeW2hG9spJ9zhTShGAkjJBlDNh7n2HvXJausu/+BYcrNN+gARa+d4dTvneA5jRsAcI3FYncKh+9jNQVynfsw2zh/RDF6bZqCr5nhMpFuMx+u6uFiIML46SRV4KLsUMJyvFDTNpxVXX/VF+MXt1bjuR8OIBWJ3tk05Srjxc53/QLnyGiSiqHR5KSCGFHnqFCIaxjtYXOb8EZYbm/NDhnJ10/TuKGualBk7kABnxsja90DaTtWtqYnn7STKYFpH97x7ywfzohQjvkuuSyMQ0nQ0DemcaWR8b5gd5Edrp714yziPQ48FeNrGLujOlRF3r2ScrA+asJtJSuBMNkSNQe6TQL01RdVZTlpry2WqWrHhKRGIOkKvQCDCEg6MXlnFwNP6dj8lAumAqrgqvx5SNdNGUr86Bn0mYFyZdXQOriszec1hGlV2RC+fHEUk7XmxQv9BJh+93inO0fPc8zGL7xUj/BVLO4nymCO0N6gbSUQJ034/tGdVZckmczd9zxBNswUAfaUkka7JG5mvsPbzpscYEPtb4cLg41iC0Wo7wsxRzzqBnxGSHnFnmCryS7xTOEfh1q1qWVqzujPYHYjD6deKdgBlLJ0enW7FSUpVfJ13Df+XXSx2tttnXygG8BSUCCH+dVIomu8kuVUd4o6wci8l0b3ljMudIGwlSrtdaRPnJcm0D7bm2frl94XneZLyUAx5hlixJGS/iLhBTYy0j+WH+XEruyEnQMtNODPF7X8nnq4VbQAu80AGfwAzjA/cNRjBw+eO64CY5YBAuIg2Yx9jVa0OW/Xe5cDlv3frnIrynNsbzQoF4btn/XAQEm3oK4vVDvIn9ovyW4ucMx2pYjGElPyAlh1+DSzA63H5M9twMYI1qqr1k4rQm4Dzp6ab+WE7ga+R5lIieH/anEPAaWjUDOL/I3jyaDRcg5+ORqJfDGzbEGp5F89ygq94eDPl1Ir6kVGJyypam517TF1807g1GfaPaY1CINXLhn6wiqo5Sz4ibjX5/VjJxVl+DLoQMcUwkEukhrj2l6fVGUocpf8dMWPMMkkFU4qnh1O9Lz4bWGN26Zd+xlmFKgdnIaHTJUlqx/pdof2u/xfUs5x1NxK86/Tb0iYq4b2toU02Oee9R7VVFaHL4xap54hzU4CdIwCMYSibmbzukbipHhkIgVGU17mN22Etz/66MXysYytd5xFBaM0Np+2Ee5i9d3IqMv/ZtkwalnPFtmXq7yz+zlWAgwDsyiqYAzyAGsi63Owyon9NeCuVS+d61MK1+IfwH/pHnJ96RD28AlGyLofCUfiD+3WMlujnQPsrWT/Z+XU+Z9foZAzMsR7Ft43GAJfti6EzFpW5yBz4g027gczJDPnkhQl+pdgn6vDsXKNsl0JkD2bBhfefl8k3P1rRiTqTkLMq1JToDjzHClRyyKoFRCSa3dLiq1x/xLyIbbv8/yIOkCH0jBiHRyjvq9H9LSWP9lkdzMSf6EZxE9WCPN4kYGV24jYaXKRyO4swVOZLo7tAfIiHUsSzKYIxVg/3mRWQLFmxsTjQb2zo2zMY2DCMA/W1SBBFISYwAzutgUAt5UKF5dGqJoqR+dQTe+S0fTML8SH0WcV6lMc7Lw+UprT7TiOP0Wx6Hd6reE1G9AD6a7LGRz1MVSJuK/Szo8Hsozbti3yl7Wl3EE9UdQpJ1paxFuRYEWu2asECLeQpJoI3JFI7SQpx1q0e0vzqFifCWzsJRemFXTC69Gh2l0cke741T7G1kT7xIf5kvhbw7LfkTgQ72mCvyPw0RZpgjdRFmmHzmVTVDDH/EtXXCvc0/cK62ajIQq7vPhWxKLHPitXrquVg+akJdsbWXdMS8B0gCEC4zHtQMrmMvNGb317GH6RSQAIwjkeVoZURjZch83UB2yzpFvne7or4+2xlSayhevWmSlPxwkpSyfzLVmYAzjuDP/sFN+bOYc8wQgz+HwiDEHRtKJjtSkabmZ02NM6iQNcAvrAF+tgbgspApoGA1Wg7KlFASm1EYWK/hjJMoEZUzlg7qNh/L9NZQfDPnAKEEIJQXbR7brFW2OPq/p6cBZyK8VoWEjwB3s+arQUvVZLe6B1axzFm0mM5Xyr22xyVTRDyE3ysC1SlaXDhaqRyC51LXAHeKY+baw8J2gGyJz/aS3EZoBXDcbJgCJjsRkX3oa4xrs098Yb4wnxaz76E75ZjLvkZEZg2pRPG7F957PoFuTMarxYEzyp4sFNzQbYpdoiJtdR62VgAl/bEVd81e62YRAlwtF97WhY9YNJNwhN0njFQK7s1Sw3IjsXOqMe2RFPW7Rn7Da8MrCDIxZ+pYmBY7VrFfUlUi8g9YHJda4x6wWBii5GvZb/aZCJKztgsjKc73d9lzSxfMELCYzB9uoBnfOYQPSUkXVG9rXIFnpQz5jYqMa1bQ13PfRLsrxRjTBwE6Op12pRzDjB0ZFJCyBX2lOJrsKbz+C3ZBPY27Y4RYipn5cdrqeoJOcW7HMxfL4ueZR2T6wHsPXNLP+hwQSWeTYEjsHKRD5Oj6zvNs+dthCkkhyRLifFHcRRGU3iyo5MyFkLfI65xcF9HVvkv27LjAUUgZSspWgz7iG8VYn1IWoegDoQTS+HPPMGnUTt0FQxH0UV0TVvWPAW1EVf+uuwR5nICGpJQ1sndpFyaPW5uQx8dqmpPHR//B5JHj6sfcaeRBrWlOH7fdadDHrhSBKYiSuuAyTla+l1pwDLpCS8kCpN/kX07PQSxYITzpgJ59G/G+x3i/inzwFoe0GnJDUfTueBXZBXh/3GlKBd5Pn18bPluU5OktOwhT2aJQfFSUFU1YTyXZu+k40PVPj/MBN4g5S0BUcMnLzt+lP32OXVQXCGNEqrBAVPGpt17bEOkWiUtMB0+3CrdIZUAuGqXLLOzVjWfQH8cbXpHrZc+3+GCzjudgyUrvEbg5HKaIx///ordKQykaCnM6hBbAG1qNcaHVj2AJTf3c1jQ23+6JT/J2d2S/90kDL3ePhtjvIwON/X6xka9jzSbUy8IQnVqklYSkZMYG0qKIzyhuTjbs5HhRookpFSjCKhSj83xMJNFMSIQRkS1yaEW1IpcUMnlcKxfeF8NqIt6XQC6xj4sTK4WoFX53MpkoSuM4DuaJyECTOLE1IkUVcQpxqQ4FC6AahV0oumoK+Zey62lWB/xwWCORp6+L1oGWUU7XU3IhxhiByIfwOt64R8Vlb5x0s6H05F6n+GPddm1ST8zRiD4gDbDT29E7rfDddqHvslY0/S4S6lo+EUFhixC6/R2FXmepGn9lpc4NSl3hHXhL6hRQ6iomdlHrm1kpbhc2nsRlLIaMYtKvIAok0YoKIYeXSq1zpmgAlcNK0bLoKRMe9ZQ3J6etKd8If+HYgIWbyY2e0ouv2My2DG9LtGWo3leFAaNfWzJoYHk0GTScgdESDFFdg/E1oFS+RXg/73ixkew70ubYRNtcyRu/bZwUpuy5CcgECOjscxGWZI+rhi9P+7WKT9w51YoTv/acmYO1CFIzhDNrIqdVi7Rm2jfKr4ujer/ltnERgPZqF+a6AKUnXervht+qxTEuYhfHUXDPAyZjG/Eo6srbeED2bDAbwPihzD69YWDcaMYkiHdiRKYZ4fCwXFjcIipM+pEWgi257HtlzzNmOl5iJdz7qDkiUnqEORwpzZGOHCm9XfbY8VFKQxRrqgzbnxNu7IL3KduRNXGdWhYVLx2S3xu199IFg/rAKuT3UjR5SBVV290DFlgJMB88EenW0uWUcGuRSquSLhffYfi3nERnqQEL2L/FbV9Ari37deuJ5pRvck6EHvDi7YLu/bm+Od07ebtB9waI6/y8h1qb/iu99d2Z2IRS60PIc4clKBcIbZ67MbG85dKDIqnYwgSm1P2gGpOKseBUgbugUBSpdst9nHM+mTLcU14xFm1kb/A8Mz6RK6Zc4sOYthWPoxJcicS0gIipQYTR6WsnZXmsdEm/Eo39l7hDg2h3b3FqEyvyVqEiTiEUH6Ng7bSNloRXekK/x/EWI4EB9V0otbvCgiQwiHGzEf4fj4D/LvFN4P/xP4L/M7LnwRD8XyL4r46A/4cI/gfaYM5uBFL7WbmwRcsoBPhby1CegE2yZ2VMJAIsCmWAgP34iHjMmchUAXMIzQkHfDF/jAPXdwIcyL4tjAMOdY0AfTeKZ43aR/0F6K9piakCQDbrFSNAH5c9gzWWfcYFQIn6uyARwuakBf/rrvjuaMVJMbIJgQIyH90zXwzxSyJNbjUsBmcYTFQvJiXXMn+MoTL2mVvVTnu0n8CMOi0CMyaz9/u5/gZm7NKEV5hLbeFSK1B4bBY/uATwXkfX9dl/YDe/5QJZIRPdahXwedKxRBCmuKkj5bS9hDJvABXkeC17PWgUrZjdJnFsJlFtPDjPEZkJ0RTvVhdzdkKyuS+m5IT+Oe2JIc2ZgQwp5Cxlb5QLV7QiM18/imfAtB7qeuibzO/TkVtRQorubUwmT4kk1EwJrWBoQ4VJlRAbI7efj1eznEaMVfCVSC4mraCtdUmNIrYhgbw+NukVNUYcJLd2qWYbrO5sXs+c2/Faa1A/ZrvtA2TPrNpIIucmIvf6o+imYisy5LvXbxG7+WhtEzqHtkbLrYbbyeBaI6+DyLcVKdOzgPM4Mhv1lB5HOZj+AXz1rfrmA+jwKFLZ0Pc7Gt//x2Xo7PRbDGi6tx69AVqIb8+/XMTzXU3p+YLRTM/JbvVl2hXsG9eIb/yepR7Wd9aFLN4JzQARU9iTVITQmKWexlDh3jOFiItSaOBpCUT5oZvRxo9gOICTtsneV9sxkcWmYXDMGaLOcRugeLc68ycjUeZkhMe71cU/RcAjtJ2JAKmWlhy4us0IWz+uQKCrkgtf58vb+jkDz0m4Fe+1xv3LBVD18EmphEyG/M+MvDL57LFgyhs6PGD+MZRGxgnDtIbzyGTSrZ8dyLnPSCRDzgTxUkQiGasUXlL2qFmRyif0Rc08avKvcDoP3000blWNSBjzUhwS8BXsEul5Jk5cN+wWbt35QM9MeR1xdnTllB3WVS4810nw2Sz1J6EPVBHpi6B6H4t0jVM4KCaRCmQCQv4diYwRYp7+b9Autb/dHHLD61cr3PDaXyC/uvxmYQZNjspVvoFK6w1gp9fUhCIAXPZfZY+jvREqiHrdX8+yP39YtiVrAQrBnk4RKrNQsi8rcWgto5Tj388hGpltnNtdXfQ/4dHoRyLwaMxNV8CjXTeFwpPO6q8h56CUMm/WRZIAPriVH0Ea1GdpZH7ANjcJOpBT14wOndJeusmgQ8Oi+qNwEsuqUUTTFkX2t7yv6O+JC5eha31D/d0Nj7VZfUMb+pEuNvSJWIob+Z839C8A8frj8LaWEe4tvk705m74v4FHHPa2pZbNRdkKWa/st8qem882l1uLH+b9aaeV9xGTtp5tTkztfQ1ieuxMlEkDz3+hi/B5gI7StWHbiqi+UY+IiplyCo32lWSqRxeBtOKslGoQeW5tI3JphC33PARN6YtZk1aH5J8DmLj9oz48qtaulNW5iksqr9qrBXsbPihbjZj0/3nhtsLOVs1DRzsKBRnnVuOz1G36ChGYkmxMS39EY+xKjfAvWWBEy/yKYRwDFgoLxEyWoF4vzrDWFeGFcd7PLGTqRt6MYi8+01tEGATZPUCvPwrgkNY7BA6PHhfgkG6+3HQu51kTC/PRU4433/X1f46y02y4UWz9vMts/Z29ja2fSi6WU8KnFCSTk9ly+dErmS0/gCe6E3VjtQTdvMirwKOeMNo3D6JEGk0JOh9s09Q2RWq1Jw/j9kaciDhncnJykXGKGsshZGf3h7LVCQkJRfXeLUQ8KchxQw3mqagryjlt/BRmniDYlSM3FZ4SJJ+hMOe2JcG7/Uh2W1wQktnQ1Owpl5Bh6n9HmpxSbgh+GHLcTMA+jd51KY2UjfVthKOUCkWEaCuBfrI7pZjyPF2LTqlSuY5/UapoJlE8BFCpZ1Rf4elCWB79jRPse8xJOU8qKSfdAVu78FkMw+bwwMDrFXW9O+UAyL6KPGSbS91OamnXeLbyo2erfx550VXdRBeCNPA9hGd7i2vmMCBD8yULKOpGRgDLuw+FEwuvExeCrAg5ZSdxthS6l7QdRrurO5QULbRMhubhebctXaurbz6K3MdICWRFU19cLAMaCHUfNYmOHdgU4nc8yBDfWttzwxWY0APJ4RhZZPXIOj1OWz/JKoyDIXEew+Y8Y/DMjgySiAWK2pilVgvsENZKFB7uDjh7mrKkHVG8WCjZRkP918NCPiaeHM92qCJiwzDNnmaDfV+eTU9vFbZp0TI3N2wR/+4pcG60IpUZbJ/C0OYebE4hFjxg8IX/XC+29XRtc+LQ6waDOGyFp0I8FcuEkm4TMXWFEFOnGGLqTBZTAXcEtjkDz0ohcfUMa0hR0urhWJKh00lCDSlKUQrSQsIBfZAQc/j4iVXVSADU3zxwBeS5COxJP4xWIlagFqBNIDCM8laupfAaeysOtsEzxImT8tk115Q3Hi0mbLjwPg5i9NSRERkkHm7dVNDdeh2bDFHQXYkecGlboqTc2hpFWosUJFmgBDkVe9q05guaCXZ2HwzTwSsH9he2MYvMT0di2SiH4YKdL4Wo8OzLSXPuplDx2v2SiZ3N1F8Zm2bbroBNLa8zjn7VY+xVpG7VP7nIEx5nqD3GEVpk7rYicmbnozg8hWtGQb3iFJUOI+eFUCnqCM4dMmT9zjmxZN/6NmjC0qVTnLlnHD19tRXL89xzqRIYZcGL5vTXD7KYwxYA4BeOCH5R0pRflETxiwIEXl2uxkxnsJuc6kxmc9bQ2FCqswrZk06bcSw61VlbBpdtbSg3USu0FRUWxjAprmvi/KqnN4vDILeJVOabgTgAgHWULZ9s0UhOMkPk5A9E/2kik5YSQVAMs+MnZznisd1F5i6I7Kg/XlElTUTNMhLfSU8N6aYrCLkNpEck97x0WtyTq/i7UA4gvBmun9PfxQGclvLHnLIgkCy0RQy+C9ZXQL26VfEnHKVUeQBiDswBNi8Mxv4ebwPc7uh1Bbi99xoBt5m+Q6j5IZTKvpdB0tePVhv2E6F1bZM975kjta77NLbIslpv8AZgDMRHDHovjsNxdfGofSfmQsk+wzfqjSbrLKV+1zpdz9bZ0WydDVi+zZb4VLN5/hGrQzLp8jGRj1dfciwcsU22+N71RqCwLlGOKJHjY9LOUH6PIxdEaHDT/B4/0zlyZdUSQC4rB41OAMqRBbvqBp05Qy6M4yx6nCq46H54yBGsKOC7SZxbJxetspJZ896gKVrGTyvWnuiFM4V2Qr5HcxyUstRaY2e02wcIpdWtplLTEKb4Dl6k0Fsr5a/x/XqRhQkRwyxS5vvC/i9GGHO5q7ZWhDHXwVwrQmHMgC1ftWT5aL5h2Z52kXd2rRCcKini8yFgCRsVeehGCmd++CKHPM83crooUgWGQWJEc4URTRG6/RLFQLriuzYUcOjkuMCFtmaBzbV7Kaq5mqIq7y1Pq3FhJIszgiiA+F8t/laKvzhWUsdCcjIJEQh3Tej6siyD2xdfJbi951xzbn/r1Qa3f/xcGL6EaQFk/U3scCDMDCWIM29SVTWGYm3iiC+RSa8DZdIDQXcCttisRQLcIwLgPlH8L7M9iamM7CnG8+sByJQLj4JAKNBqpkg3f97qFZKaN2wP0hNOhsCDc+jkMIFdExsKAKAcOs9FHRL1PBA6JDKOgDrwhQv2uZy94N2T4ewFv+kn9jcXosa4DaFzfM8rkJt9PUMeUpFHO/1qDHcUwwklLRjmdSRvrm/uhkLCZy47DyE31J/4PXJK3x4Mn3sl/9H93cb5V+FB1GQXGfHdqO5zro2JvxF1o+UnsZdYuaB7zWRgYVg7DTCjjzvBnm7Jbr+RWnZjmB4aRwn6fnKIq0I2I8NS6E9VEZsjjdeNWCM7twEQAXerybJrcuFbhOM1uWPhJResWKQ04wa+2h7nf3UV3RaZrAKXTKgYLoX2IbxvTnTKK9RewAO8KbZkIC6zQYrUTxyL8r8N9BOE9aTsWX8MR3qMEi2ASLX8GCc8ei4inx8m8wElz147aQ0Bvr1R9owI4msnlc2nlJQ9UAOwX0tJrQZQYOK2qg+jbd/GSP2WdjBw/8AibdttmICXbnLWKw5xfGtYtJzcPSxa/mCIlosjRMvTilSNn8DN1R8XonJiZtruLPUkZg1MEvdZJZMf14lQJmABpoRf+rN0Ffs8EZ69wxV4UIoS68IgeUVBLa+PoQ7RwZT+2OFwl1F96fvOiylFqFD6OADRVeR+vUKYnoV5uXCBHr6cG2FzEbu4taKkFUPKw2S4RITDV5CDhbBIu+xBTmMfFt3+Y+JMnPKP69A6zX4/jRhlJ4zbQ0UMvLQZuIu4dsiIh4cN/mqb8uSWFlFB8AbPnPwAkEKyhslDy11qObLLWRQFWRwO0epcF+aZWno3wGyDWRpbnyXVanK/EJ9Mbx7SHsVhQjHt4qjhsmHtmXgsybzGLUz3epZ2ZWe58NZfZtf1UXir88tEkEAUtRGN3W/GFRPUQxnwjUFr0XpjX8a0tiP6RHlKgSytz/tFP060dj1Ay5PwC/68uuOycfYjImf7h4H2aUEXwHw0QzXgg88P9I2YYkwtCe+HWhOxHwsShQSj22uJ3QhZaNg5cZc8kMmslDr9WA1DJaPXJiVlk/GB3AkI3PzpnWzaw/TFdRg/bcX0xbWcvBgBp4a0B2ttmLGBnnMWRbJhkmuzdm+gX0uSzCY+Q2F/e2soaFgESqCRSv8J/hkeiPsxlMdkeQ1L9XjnQohbfmWshl55hCx44dn7z0fM/osu0OU/LkVMXG0JdEzPqeH7VGOmteB7IiKvYlYvOUY8oKjn71cKjls7huJ8VyYiLevvv0DhvADC8eLKcLRZaSZ46hl0XaYEU37Ta/uaExquoB8igbDDcylW9j6QjJcWZ150Bx5PxGDCwFNrkrL8fWzQ9a/n2IF0cRf60uxaKsLk5xQ7WpVr73ahlZhTjPfLOFpVuOzH89agBzBdZlHE30KUQzAn2qO90JWyjH1joswIeV3FRl5ngo0dZMpHMZ2frjLtw/iMLqE7ubwjbSAOJ9EjXMn4LixGFBlp0FPxOX5kFfo2wXYgUdJaQbNyoNcU4sA3u1ouDRGhoIb30BxosMoEO5Z2IhPvejykFXahUO0+IvaR6JaZwqNVDcp4OzInvLmUpZ5yqGsqOFwa22BY5GQjPtIqOvAKNXSpKR7tiMB3UaFN2YeCVzxqLfFAo1ZwcngtobPwVrh4DYpf5PELfY3DDoYH+iUpS7/8gv/DtCkBL3XGoed4s7g6h/HR03izPH1BEo76eDmGajrVE26O7xIir4dc7jKQdH/LXhno1CE8WzERwW8mvo/eFBNOULXSxF4XpWdC3uIVoJlUdmJNFCATSls6Y/wAWjzb4IVgIP+Mk4TnHgwzFU008zkf4dUiPcVZeWqiP8PsUEuwzxyHPHVHjjx1N53yBqflMzABUmYHCUXFeL+ODXk5+YK5qVca69XRY7XBWPV7RWIZIP4TYAuyE/2T43BlJnAagG/4A93b80Xm44zNTNuNQlwSimLxLnW7+pQtFTMW1iuBORxsd3IVk6SdWtsEsY8zE3Dkb3WhYBzrGHnWq92Z5ceThzvdvubbLRfNSaCzVpSmvo4X6+L0j4xT/CMp1WpRIbGIjHjngHkEg3Lgp0Rm2kV0LegOpWSfheQVtJFkxCFePJ3ItnwrULFYt/+eeEwXWngafZPt6ya1VNR7YB7rREbXbCsaDWadJ74EHW51qqN4sqlKyUGzKxCXGCH/Zg2wyoWrjIMFh+eY5PKPtJ6Vn3FVO9VsqGiQ5FkfJ/JJRTzewr2J48PSiqsGyFfDAHKt8ZMUZUwDjNuslBw1u6ViN+iC/tvd9sZJd0JPLZ2BUR0kub0p075LnvUlbueYUteYDYERphjkiK7AQCs0d9i3TPsaO3Gqu7APe+NESkETL7e3ujD65VHjBhNFHRmveHSY804cvscRxPwgo9jtkqxBVre6QSk4aMLDLAALlFZfua67cYcKbAX/kEbZJufIz2Qk0XXwijy1zLgTvgRnWkyu+HvicSGVJOeAxRywHLizK5Lbe6RMX820m/XnuzIGXiH+SX4mBqeOqBjTGTe42hmYEMR5OjY3uqV9TvUM5ZCTDigDuk2sdKtWB2oJGVa8z+ouiQnj1It4j3q+mR0UegbvlPjiPEX1oJBCd+E67OVu9UvkZQ75nnLVQ4JHcW4CikzLk4nSHcEvaV07YGce6kzHaCMyMi0X95HAuupHL0Xo0XQLS53+LDoulxxMcoJU2KpMwHU2wFtGHKxedjz8oyQN4HAJOZALPC6QJflOTLtd39UxIh+qWA/4Mxg2NiMefyTBjyTFPzFVUSekopfcGAzv1ALjgpsvKU8Wp4PG8eSWdLdU55YacJGWK2qi+jOAZ7xTzeiUI28baZXbZyfK7ZVkQL1EQPlDuCd4i20RsAXMLDkItGzoeda7ZuwZO3UFerSESfSh3Bhh2vSAmRW5RIdahbvqsreUfWNxef3D4hyeKinTP8zq8j+Dob3ZUBcPfzPgbydUtlz+YZT7Mx5+kCNBEvxIpVM6keQney2Qqkr/yB1Ov/IbzD17H/yjVDs8FwDNkjtwdE3qKkawTGCbdEHhwxH4anfenD7pUWXMZpxEeF3c/pgse+WkB/9gfV+AkUxODUxpJTnsF+RZL+BMx5QoY04F3ICIT56AJel0M/TjsG+YNpfWvR76hl4nfpGJYUfC1ztVJPhxqwAXE6yAi05V6WRsABqfJ8dyGE00GR5u5qv94k2RlNhp3AOO88ZkDBOEGhjPEQ3HQqS4UDZ8X1viRt1tDZHi69uwK3qq08gdj4S2MZa8qZPxFXTOtDPPl2f9bOUHoWs0wwQ3VRDcl6xMcFPRuhGPFFeRqlx2XS48hd6H9p1IdP+KBIjyHTv99zHRPUVEVwKiiwkVFpj4qHoxfeQg4HjZbKK3S0lyQ1I7Dknt3UBq7xOk9kMrr4WVSG1aMU2/KiMnvP+5yfGThiljzjC9PcL0ttztvy0L6O1A6K5FYAqRW4e9QZ71G5Nb3GUit4eB3PYDLeY2JLffYB9qA/QA705cTVtM1FaXPXRflDoeCG0VzFMnQqsE+eSeJuYXE4OlTG1GbqfeQOmfQLiPpUXACMaUzdpNccywU52UPFIdmSiygtIZaS5QGgkvGJLKXPY1sicb3g1T3XgrUt0HkerKsxxig5Kqbvrj/PWwHpJBf+dbLkt/TyMTckv7lQFpEyv5rmh1JFDhbQomSrO8Zmci7JtjIXBmQuG9XyIo4qtrnervCGbDLHQNZ4a0mKRFSq1eS3JcVTrbW+bQA4PAwCiSlFaVSGO884BCQTck6JKop6s1gjSrkfdFwHbo30fSZ5IGq3Un029jgLzkKKVivhXvJ+g1gQkKWZxS92L8ochWGkhYpsHSspSmbWgNWmYN5oXaq22KY8Zq9RWra2Q1NZbOO8JT3iIXDY3jKeMUI6btaxvktKY4GJoOUmJ9yXkj/0MURQH1W//0Ao2fli/X1ofW7vXOtMZ9FM9TtsR0Th35ZIM4P0aBm2DsJM1VO5MqBov+4L4Ysk8nWNIlWIrf6Yh/JhFVzsYgL3oZD+vzXvQnbLmdMzLgQmHsJ0iKLoz/vB3PVLjvLPUwqhWHUOO4drC/RxLe5nsHsDXPGsn+6yTMETAHmoMOZcZ0Ub/jxLIwD/Z5f8+/A+vF5qtAWvP3fECUnu9Cy8JbLenvnQvn6Q7tSt+jYqdoz7RbWoU35rY2URvzpmSKXri/JDRfuFvqUT8FkcYtD64iJLoawChTrXYBLmRJ+7IG9LHJhUisI+8vcXhOApkC0fOsgxlVIxCpm4GUo7gE9ImDr6sywvTJ3YPkwfVMnxCz9gFyuf2tXPZ6kgclZ2CEkAe3ybOWm4Q8uIsJFEmoPaC5w77NkAe3QB/w9sRSl/080CeYwEmXR4unEXv+wpkLqvoLWenP0bLS1v64j18aWVCbikxhWSlSTmLsQWHpuFWsdEhiqr8QaR+FESnqWhwREk4YlJ4TjLafigQep7jPiAQ+Wmrr0C7mtadwGokV4VeWtA69ob3cErXkvdo1LdjJLYJaMhWNJJnpUSTzrTYRJLNdrEEyb8/5L0TzsvQzd+x/oZ2/6KsaQnRJG2MJeXP58YbNujaytzD2Moza+wBsmO4y7qtV1+qTG+i0o49EsNy3kwHLVekRajgD9acNUZt95Nb/cbORnrcBiqlf18jfNSQS9BcZADxfLnyuFh5/Av/4HwRZ/E57qRzY20qIBYHBkjrU6tsC4n+X1uKmpj9cP6Q/98EH1EpMrwALuLlBkerUzWwRrFcGpEz8VVGTkfHougiZT12FwyYgqBgSRzfZ/KeFgBhFjV2KNfqDmLFhUb4INy8KUX71LMgGFu3H0AuIGq/UkSEVxSB1V1oNtiTp1JoC2ttRCwA8CEIVWp3ZcHvEUaispxoXcOglwJYchpQwihzXx9M9J77Ntc3FAxAd9J21mEX+PLwUZ0NMQXD0fcg3sve7RaAtXpYWsZM9boneyQpPKL8V76n+JIDN5o9FijuGeLd6VGDuEbNWaomc+qHOOJbVBja8sgrHNKYctwIAWbdgctsI0miuiySNUfoyUsmZQAMuSxnfaCkoI9NFUJLvYLrOdNF5Jbp4RxO6OPWuK9LE76JpYnk0TdQfpsOYy9ClwUHCKqu0qjXhJ0CG3h44gPZDCjpbAs90krdIwuZUugUtSz1KbLPhMmwzx295J7UJ2yzO7Qcvz4Rq4JRpJ9DigrzyGmR3aO1GXrkGeWXCuFSDV24BXtkzsxfzxPntkUPeKkp/IRfvBCd+Brp67jJDSLz8EFpddghVpsghHL45agilSfzR/niPes9FonSqPXk2zyFDZ25vQ19Qy2BHLIp6XpHOKv6XKM+fRbvfhFb7NUmKvSpPN3BRG2RCQ/oprT/9DWp9TXy0XmwYObXeMXiqpRSsRrPww484RjkecfzV8bcyg452NzU9TcXpAj94zSROU/0WGWaj46We2olg4+Vbjw233n8TtD5NEc2V+tfouWNfkyUP1gjwp59qLhP8h2yMfyAPbG8G9SF54N7/qzzgZ3kgi2HfBbB/9/+TPLC7ryAsg6uiCEtZ3//RdqKXnQwGZzfDo6q3Qiy9IoqbPxaDpnRk5IsFIwcyM741rX45bAtZVrVRjY1BYR/cmRAySI2yTUYTk9ufkazEjqTQislZ0tos+8+yZ2DLSJaO0VqG7elW/UKr8M78d/tTYqs/tD+5B7RuYn96s49Yw0Y9vIa0YIq/7QvwkNbtczpDhHVT1LdwRdUCYXpKoi0P/GAYnzCdkKKWanNpNdwoUxWwTPWeLjj+lRg96RQ/nAGS9dlZom9a7KVGQ75o00LIFzEtLmeT9Y2hu84S6ntH0bVrLlJi3Uiiwr5Pfsuq3pclLIugOu1E2m6kKzan33Zjpu+QrM4EDchTJtnLiLDMxFc9a4iw/ObvOb4Hk5JijDvq+RCXimzo82HYuZH/VrXTbr3YyM4oLUWGCyuhMADP5/CE8gXpx8PylVut0yehU4a61pAbEJWBIS4VDJFztYBOidLikzXpTkqfhREIcgoognLKCFtGjrwNOLz2JgAl5sOyOsna5yvGa8yTzspT4WGO/Aw1fAbf8SKNdqkVZNqTXxmJ7vZj1qCtyC3V6Y8f55P5yqgLaTFZIsgQi0VC5FR4HY0iC0wiZ0o9qnJWYXN3p5zW3rrUyIaeP6Pq6nvTwvezj5Fn/U3sbypKFyxlcMf6pnN02GOIcG77BbnwRry1988ay3dN5Q9vPgoAyBdvrIuU16VilCCS1aFxylyyjtC9tOVaLoLbCBaJkil4uEL2lsnC/sG2IjXdkAvlVzri2eeYUsIAqc7YonanmOp2PvbHskuLS40RssugDiS76Gl4oPxXEkbL5ECHluJQIDCEPrp72jW6G01jV18G/1GQbo3ugjsCI1n+vIDy5y52kWlwD4iZ+Ktbhd1SrPp2EZBqDcmfSeitF1+RwUJoCsIj58Akmzsef6kthDh6FASjwLeR8ii+m4pQgAIp9abdwBAte/O0kECKi8vXwMRHS6NPNDQGOejBjYgtjEdJqjdaLF12xBBLd8oeCsBRRwqx9Gjk8YBL3anvxHCT0roQAYkzCwISa6bsOgLGGLYMWJN9TwD9wet9RiFE/66drjeI+ow6/JUw9waSVYC0VF+GtLTF8AXL2BuYtKBntiAtCrz6AFSrdPPmybQTWephMjZESC95LSKllxtuiJRewsaGhIYuEqoa6kdo4kzQuFT0+imOZQHKvr2qtbautrFJZrIdpDYEtbvqBKXBBbDqD5+6jNx+E8XvW6ZcL1jDwYNR7HUs1EfI6hGMVjBYveDo5WCf8mAi7ANJAhDQzLDr6GNgZfjCL2H+JhLh72ER/usjUSJ86ZEo+dZzoTGon7sQLd0k1zeXbtBX5r/YOy5I/9+Tby7YxAY8dqA5b95j+0PerI+pM+xNl5NvQlbbvWizfaGmMWgcuyWGDtD0ZYc4EzoZQaTyLIz7vhn40xXRp6gE9fzrT4l7Z/nwtbYqXtxve+v5K0iuX5xvNEJVGv0JNpgZsXg9n/INWc5ey0H3MKp8dooakiT7svYDssUCMekjhK0XyfY7k6QK/Qz5XVUaBI/v0azUTbUEQckCghyA37oteBkcsJL12TL5WrEFe/dF4kDb0VBfUWDggNgEsQE6OrJcDvwRytGaj3igtahtBv1t2kRD/601UdDvRH4TWGHw3ngjp3YGLnQSLDTGkKSGGW6GuifEcJNrBMPtj/5Hvn9wxsl4YLizYpjhJqFPeqp+y/kgC694SgXU5IRbPWw4Css+tXU4G5FLPacE4jKi3RzQ1oHeDQHzn3DYrpTVlLztyz0kDcWhC4TDczEeyLeZflllj5t/mWXPg63plyTP6IMWl8K8PWhgxhTx+J6es4fhSqL7+pJC/JsXFhj4t+cbg7yaGOlgcPBVrUIhdcihgIMLZiq/shnNMGPKBAc3YGXZfnJGQU8MttXrB+DLWt6ZEDP5mySYyYNSiJnw+sm+0yC8qntZCNW+Pmvwj2FniH+M7CX4x4zTl+Efp4h/2Ho14x8omib0upxo+qoUKZqeTooUTftubA/c4YSsvo/G474ruFSkYqTd57GhfEohPG2tvXq6KYbuYAHVeiYCQy2FSQaG3g3UVnv4dGhltv/GUZ3eFrEmvmf9lD6vmshIfCQZ+fOlEBkRC1dUgba6b88QfsYL/PwAdrRqI2rX26sbRSzA4uomxw4RigSdQPT7vbnovbRaiN5PaE1E75tOG6L3vVrz9/KN92xN36upNt5rJeRP7f7qy3Pdo9o6o7HfMvRqUM2HoyJvM/p+NDKdGC34Ke1N8cZOfUijyO+rnT3VtH8cKvY/Ptz/kaug/3vPNp/Kd6fE59STTabSOzSVp082f+8l470hTd/D8fB7yXhH2xIKrWH6Sxvx5e4ooaTfqSsJJV8YHfkTusgMWihhF/2I979dV4uGuItJ8oyOFBd8APgtHqk646vl9jOJNMjtvZ3wZlp9yC48YTug+DHgOb6OLq6gk2pvpzp8fu2u5vN796SY37kTTebXMTS/nSeav/e48d5/mr63+6Tx3usnKNR9RbOIbewI4NYcw0HWKnet9QJg1F/fCcDR0uh99/HmwPHCSQM4fjxOE4blSERXg3hFqiRvA/gnY5/cfp5Ynjm2ePo7k5YJl2sfLkenneTnR15aev325nMsOCFGce3pJnOsPWHM0XpaaFnf0Dok5PUQJO4qwMMmBK4NOvBbhvRopnujgNyvR1hA3k3ncdGkDuEqTOpa9IgkdRGncTvjWB//F2ocPSu4VPTqb81n99FxMbvc35rMrmtodn/+zZhd6Fwzgl4+evxKGLn9uCFnI8G8r7tBMMkfvsk4uhvjyAo2GcerRi/6LZF5iBPadxdrfNf+ZmvcB+Uiy95uzdY4A16s7CYxZ0dOAmuMK5wkVvj5J8Oru6BbeHX3wcqSR6K/70ttkIU8/5K/7zNtmJms3IcACOoSrMb9VZeV705p66sE9yCFV39ZvBMP71xddaUVfEO89Bu+FO+3tIUh6SgZG587dOwKn3s4+nPsQpjwe1exZk/tvQzrfQgvabV83rXZqjnh1be7Nl+1MFwGo1jw010j4DK8ckNaMyueRaw4jUtF+/eEp5NwpenMPBY1nX/Tbe8J7YzpHN/VDAR27sLJ/JbYbDJ/ghd/hmo89MbE3+QlGZ8GQt6p6DnlRM3p7cSIOTlZaIX31PMu9ZK/57hWjHAr8FKHng9yqeiBCFJLdimG9tZaX53n2TkK0j/TeZL7yD6ld4G3tVgLhoRUwa96c8gLFPSSa3aQfZBlLH3ZUSKB8vdW+XtnfGOOoPk5QPPxPm795l/oud8KHOGieAjPLuKzjr+E1/8N7QrrH6dHrf+dBj8W37++hvvAO8fu064EzRVaBDQn+y13geKul19iBpnkwKUMQgfxV+xguhYiKLC3pi6SkNrVk/r9lHA04WJnARE3Nie8XYjwru/cTLJEorC88x8QhX+GweD1zpclCuNaMmhPQ4Lb90EuFX3ym7G07bQ7jgoCd/FCc2b276MGM9vD/iEGaTAfvZI49cLRaNJwJgEWc0QEaVh35LJy7Ckt42jUXiLBJep+YM8VoHXakctBa/2RKGhtEXWfwRXiA0Y8cD8e2RYcHxkfCg74ADfV/2I8tUqrQedwLQB1eOsXaJ83JrALfMvy/Lcwf3nI+/2QYyWaAbQCaJuZVhzyYVfUMtKGHKvQg/2ewFPm7KyUCkxx6lYbgK9qo48KPbAYPdtRV5K9F8hhPY6CgUo0EOJbmsljzszZpQJPoTsQ2UidttSsgNPSxP6Y45CfyTSRf61LnloR9q9V5KklWfaLsucbVJP8WSan/bwcOAxLHHgJ/UYT9N4witnoz4b2yxOyFzMMklco2S8vKdIO9SSqzIq0xz3gTrRfWtVLqKThPRYdxeK41fkYveXyrInPsq+RfU8F+Ww7mXLx4NBTXepaV0ol3STdCrNpFtTh+si+TY3sePH8IdwHyzLR5RReb+S0n3Xkw8nxTQ8nR9INS4hF/oSJHdEKl5sGXTzTUTKFHImS/D2Sfbufv9vhWS057L+QF9E9HQ0kKs7b5+/b20wcNc/ftyf/GqoUrEYISSuOOCnU6g4KMBQAnWvDYU88JMDQn3Cqg2SqelOrFO2WRbQ7pQ032lV9SPnfRCN/VKPrjEb6BON8+Se3PHg/+tSWIhCrukvd7kJvbmmne8C1cuHndGho8pyQ3P77yZrmqvZckuRZh0QyHfJw3CBcXasGGfqmfWyb+EmZEf6NsM+4w/7rs+y/0Tm54d9ovyTP8pmEe+Mmw5tcCfRrA43tv05bzN6N8D68ObEcuZI1y/6L3N6aJQ8+4PLo8ThQsqcBAgC1dhUcRRdGTEIwa+klyv470K3WkzHMTaEHKZu1Jw+yHQEk0Qb9tdB9RtS7olZXvYvOeP9EDRY/1QY/5TuR+x5+Tj/YGJLTMqUa2CQ3+QiPqUFgTAyZf4QJVDosjECKOJVBaKWbtZNkLwcGlhGuyK8cvsgHMWSr2KGfgaJ2YH9I8U68KNIp9b1Ed4akK4EpNiWsdACw0g24mDpFWwZbrR+hE6rcTtnYMtuNMeo4pD2HhBFF30ZXUazVv6DTqrbvxkuccSH/ouizOkNe9DXzl6dwdCGEaPsotPWty30I4P2v8eieV5OZFnQALiNGorCh7kJDRnGuzd8nEXnHK2SXrQAs2URYkowf85QRlvymYAYEPJghgcOh1vjbnjPhB2QVzY/+tge4VMQh/2NR4fwJPxWPU0oEKv7DPob4LmGIRz5yy34G+b28tZQG028kFiXRiBjzL06VLrunjAZJ0N0T+5pj4ynt0D6BQJTOK0gikhPD/mg//W3dMq7ESb1T8Aqj7Hj5Uc7cd4VRxjKeeoKx09owvyE4vSzTWWuSBNPB9Kvom6DZDjDzEZdKIvRr8VxnXECprtEacY3oHso47cOLjWjJ6URabIkWi4zaHViAtyfSpYmugsN4h6LLvsYtD9Po4kT6PVgDuUI6gWo9zipV6wpoglxIF74/o+8J9OutqGYb5pktxHgmbOsKzDKZQGBAHRnzw95/gJnXrANMm9u0w/qgvOQbvl2yVHOIFt5isnvSXbZJ7sBYW1JWYHELiTw0qpWUHcvjxalzMvqZ0sUpsIHX7uWFbofXALrwToBDZNd5cY9As9xfCMW2RqnzdFcGoFAirEwPylP2MCxZ1efh+37Us/cG+t3ktvezyR4b6X+gCdL6Ugda7/20GrN+QwvYPBOFUjg5TiCZBk/ToDGz/5wY76Q9EeN9KzzeDb9Hjjfvhj8a61cAXFX/pu9xtG/BagSVCN4zW3vxdyG+DWgkihkXgs9ETRZrtkv29uSnYotvo0nlteYUTfayiWZgAR9gKg54nLQsnuQxmhjtg3Z9XSOGfk8JsjEtJ1KeApZCMknBcWuLiItWd+Bp5wW6zYOuIzmPmW80Cx46H8LQ+2oL33poahESuFJhuA51jedCrOz9DYi+tglP+AKD/rzcZPoxX4C1EpgbAmn0ecdrQe1lijxsh7gLFH4P3qF14qnnXiWkN0Wt0CphS5bliwwd8r2Vivorrvdo7Sg2FlZQdAa1+Tn3Ep02weY7OYmHuPG29jyHHBqXOOYPamyNV4C8AKTxRGsWUp7GG0Hr0B3dutJK/HkjchZHyckWmYGpEroivfY74i4HZk5sT/lLrLzL6jG6TGnVSSxs3Te8lfM8LFU9iJIl+1toy+i9U9pju5EX8FdQiM4QKSP/spcA1nuNxPeS1tGaBw0xVGp66SlddooxkyXQsUst56tOvZxXLVPMp5VIrpb3pOJZiheSAlvpZdyrKwxnU2wjMXnPSPjQKEKd6t8ZdSZDXzVO21+75v6b0KMGhznpN5yGk44CZPVxgAJt0S4DNXyAGrn5bryaYY+m/h6eqL/nmw0mUmjRqTV/kLcVHZlQxnC60QfBjsLCLXyjj2bhiHACN78At4LVCKplCMqw0xgsHhE966to5Nj/CcIbeNaSxmDk8vH5A15RrMizniR+wYPjfD2W9q14zdqGkoZfj/ak0Lq1wkMdO+CiXHiTCLScIEitoqi/Y1y8Kq4cEtnshx5TUAAX19zAJ/5jlUzyEro3CaOruljwxEeDnU1b51SPUX5LdgPBlf5hl6FWUOCEhdIflLvsJyd+R9/MifQ3z5Jq3VK109//hnqRyw1Pu1SLSHeAA5Vf6UJxKDxpfXxjpH7FrC5cDo/SWwnCj57caOQ1eslQrLT03Yj3q3W8jwamsCWthkA/rVjbCEPXr22MuC9N8+8IiVX2oDjPSIUfaqnnwClPQ5zsracDoOvlVxbRj/byrO/xh9ZhWXtQLBT5o1LZ84mx4Fl4ntgyyIHytA2w/LDs6EPSljCnRq+KjP+o4Jt3GeQX0u+o+/CqtrOckMB0mO+wzdnBhHg/fVP/JiyHRqyPdikMdyHEpmx6LSLiTQAOR5oMfNOyLuHSlaM79XAxpXjMXDly0oOKZ9D0FkiX3D9q4fMkIBz67sYgvy1f4qNl8cq1quaQTm6uk9YsnT9dMoG6dq/mKGicVrZOmloh3ncFZhgp3q26I3JcvC50e5exLvE5s7Xd2wR/uveiYV6gfI73b+cl2aPfdjFifz11f5O9j4XXx9/z0xpG+OEY/jPodQshfP+W4TXik6cg2ydW4e12WguYot4NRjc7N0H78zaDrLQiCeETEpktT1iicOgVzCDU+kIoDiQgUBDzAQCV0sp2kuafiEtdiwQhYPl1MXMWdECioOirdxq7oU5oyYexdPQcyyH6PzB1L/VzcjlkLCV0BfYAVPU9H2CvnkGbzZQs7nUoOShRX9VfMC5nDqeNE11yV6JfgFXn5oiORjaisaXaKYEMsLnOIZXTdjrs5U753uoCEDBwR+VX0qhZrbZzJ5+DJml7d/CvVApAv28HzRgY4uSC0JYmGH6xsb+KfS2xsEC4LEiHOSe1t7YZB0ZT2C6Rrg3FKpCN08kEhuha7u1UyTjUf963+N4prddOIR/Gkxg2ua28JKPtwFa5cQOT8hLD9GSYpIAuMjAp9xw8qxaysLb4l0a0S7SWvVtQUDtj2AE5vqf9RWNfZe+n9UzNEw0HmUQcWZITBJ6UUlegXwtt6S9ClN1kCt2pgmfWmKBx4s9+S9w5EsiTcJ83470NsahHEEX30H170Hu2gaPZ2ucgxaildD8q34RaHSOJuF7oMXvSCJr0bEANQlT1FOph2pAdjKXZ2vj6CCzNRl1rUjdVk45FI2pBA+FpCfQ/G/p3BV5hPAWpQr+jLkxvvJ9CQcvcity3RBDSrwz/q2H4Y98pT12c7JsK7RiblgKq6vUInfYSeVZsQ9DwoK2rbyYPIv+Lacr/KnHJQ/zvVVOI/71Hi0RJ6HY6MeznlNb9V5YLEhGE0nLdwIrmnTGRA63aUhKLzbxS8KNpfv2ZemN/tSe3GNi+C4WIX8V0vLPMBosNsbEzmJykH80hkg6PxmwiPcXUmtDb32tD9Lbe1IzedpYuR2+f32bQ2/dr//+jt5sbm9HbKD6E9PbJzQIvtzaG6S2i+YHNwrqq/9DIGaUvS697G+/Pboii1x9tNuj1cw1sjo0ijx//EiaPCuGvZclXTcij6ZcQeYxFovF/IGnnmTZ+FyQQPhqmjQ/9X3r56n8jjEWCMBb/YhDG8q2RhDF962UIYycBf1WbxPp1MDehiwWbm9DFZO2mzUwXk4kupkXTRe9/mC62EuTI2z6aLpqBLsZfiR5+vMmgh7uRHl4w6GG0fPU0fF9fXMeqoTa/Eg+468PAEQVcIn93G2N+LS7Qa0kGjGgFm4zz0CoEnQjNgHsgi7WCYXVcho/8YmQPX7OZVAW1VqQ8SPZLRJk8DcJyNh7Zc17Y/xpxex77oXSF7dD/QkAphpoYIY89vFGM93syDMSG8OHMJuO0AdUMtK/M38S7YaXduLMuajdqFvJuvLhF7MZVdVG70QJ2o0PO7CvtR6eNxn4cwbi2ViHi+jD0p/dhkWT7xUiB0HcR/e0L6hkYY2Fw+he1l0G9lM1h1GusJ9QbsFDovIR9sNE+2Fq1Ald4aMz/DfMWEu0eNOAiYd579ex1yHLJ/6WfsfWUADlZwmvZ1wLRK2GiVyLfU2KgHtl8XrmjngArWcvYbODf0MpI/Fu6ycA/uej5YMS+t9P+8ZPYbWtME+yL3dhMKln0c6RUcnM09rX4kvfbXyn2W/4/YN/1Pxm7vROxrz5CnkVEux0+rA+5EDXybzeIkc9tAqfDf24Kp3U/RcLpdw1R477nCx731k1i3G80RIw7KS/uSmOeuMEY8xh4Q0fMixIiYqsZEF+Ar+sZkejWQatZ30gkhCbwTsQE0MFIK/qJn+IsfuEp9I+awlOXoqbg/5ynEG9MwX3pf1/6L9cb08CM0/ptlwRxK4Pp6XdTvB3+qr8YocL+eDJShY1QXjHOvYvib0f2Esqmh5cpbJZfKzbiw654nqhean6ieO9PzU8UB/xEZluzia28Az2XYnN7oJUXFuLrBZjva0MjpwjD3LvQEOjEV3WmPz56bAGdpq1D2SVJnDzSHvLJozvwVFy2K2VTxMnjkfXCRHAxlumvVfbqtBkDrZgGlk4eh4ROHqcYJ4986DjFEs4vE3HeqMhTS6PPG132X2TPF3TemMnnjf1jjfPG6/R/xhrG1ej4CeP8ce+Vzx+VAZ0pfoLPH/mw8ZTse0bcEUlXzoEQUk+XQjTIhQ/hNAvq+ZxxvzhnbL+Wzhn/VGtqes54V63pv58ztq41GeeMLWtNf3zOeATT+YXPGcuOmsQ543f86/LnjLMrLnfO2Hpt6JxxBnRb9aY2ruJy54wHKqLOGYdUXO6c8ceKK58z/kh2TA2d913SDjpk/MLUNN7Fc0JS/JOE9z6dN6Y2c97HvFX32N3dKY9KyG+fzhl3Cr/9QZF++077r/KsDc389ocH4rpDc/uvnEfFqW6BLtBtv8xlP8du+0fQf4BOGcey137eeVPoXLrISYHtZuSb68j2YnnwPCWs56yObr+3ktOKW9qFX8un4+yCfXhS6bbjWWBgJr08AsN0SvDMMvrAcll56MASLwL42yWxrufY7/+IER/8AI5Qrdb7X8IjUJhAG3yKgO80HCGKmp5f0gmVa0wNf8yI3kjUhq4V36QDKTq6xDzGTU4tv4o+tVyBp5Z91oTMa79dELLX3ov//dTSvBbFk6hTSzJkojd98loRb6gXUb7sev1pkncSjp41sVPM8IvNnGJujz60XHgW03jmjoTN+Pws3cepPmWLZx8pq1OtEW5SxeQmlRzlkriBUG7S2TDK/UaHdf6n0JNkq0OtQU+phDsPkdCiYrpdf0IfLhUtoimJOyHjHeovhu9J7GpxHhj2PUFj65TVEeeB8fo/L9DdzokO9Tx8yqU2ov9L2WVPEgcbb8Lc/G1XgM7LaV5OutVavV/wCsOYUnbZYZwvixpGn6ChHzseCh09FhxPLCaFPfWMyP9oiREBgw71UlWccf9r+zMYRbLITJJez1gqLU+iEkUUuf0fYWRFpi+Y292pNiiBb+kKicAKW3w+cowDZu16hCrK3wHKVt6XDs8RKe8TB5CHqVez93+g/7T3scPJVu1lWAfKe+gdQwZ4QIBhpD2cVAKDPvqA9JbpZXgehTGtgUEvg8Ck5UEFXg7kddEpSAPav+nrOApijjSO93CNA21vqENRppHOuYwW2oeljbBGz3ipJKego44nKOX+3RF4qBFlbuqmhjtyB7ydkqBcBcs+ORFYyiQLcMU4vG0+3m0vzr1FUXWiaf4RUDkgO37S9sDTEqa6i6eE1+oxnA50BN/phG/kbYSZHJxPpxglh81KYJQtXptfiqN9qk9SlH3lfivdzz3oZ27tKYvXnsOG9t/zDkC1/UNM66WtLoGqgtW4w+qOCCaC95lWYzcLKKnyp414fIHLOJq60/pAV1XllGGwapWxNrBk5/AW9Xi2108uoWO5fvxGA5Sqphvju59eVTzH4xGw47SLCIiedLrMOKH2FPPRluWFb6PckrYbj+XWYXee1fEwzrLZofeT8P0e2gp8Xy2lLhKBuPagxLQoQhbWMNW1onCzXfNwL0nYS1R+8ePpNBI8zYynzjEleKo2pkycduE12BUmYgVxnjoJBB80Ds36RrjJJHm0GEwIlugKPG2lU9+swFPl8eH9eASTwl7r8Fzsmxef/6L0aF7r/Bdj8GptQoL+d7xPWYS0b0v4WO4jieJo+uYNhMa5uc/Q71T4/YzsfdMkniVB+R+y7ys8XcTOfJ8QpA5qB51p+iqc6Rqry34iLx/TuSRSuDXdA44EsVZ7rhhQaIc7lEAN1iW9jPEfu8vzK4GEBe/R8L54j6FoDeDgoJ1Q0G6El6Fr2dcLiEbV+4Lf8DD+RmRoUMF7REut2l9XibZonyGRAYcv+x7BDKMvSn/PzeZyFpdzcsdxeRCXx8m+W+kX9p3Cffc3+o4x+sYL3ckvg/Ks4vi/gHbL54h2u1aKdv/EdscbI9q9FtnuG6OdC9utNs6hAoNefZcw5jV4rq807CSwNM+/S2u+EB8XQ4P2uO6BhGeouv8/3+XkxIPehh/a+ZX4rP84fmUuPdP2ceWfufJVrtzAlRdfp8qXuXIJV8pzqNLDlR9wpY1fn8KVM7Eyes/1VhHnU03xZ0rxlfDnTH0U/gxZ+Yf4Y6acaQJ/ngL8uRbBRF3D+PM6y8ldjgt+XnCZnCUTgN9XcXK9JDpNFcm+BuC951XigremUvMTkVLzoqoIqZmygfv7Fv1GAvNEf98X6JeszhZZ2ZIQF05pT/7IuPAU40Ii40LYPjRgRVOh2grY+t2KkFB9C3xVzwsacT5tRPtZEe1PaT6jvT6J5Wbt4HKhzyNWRLX98wrDTvZAc38KWG+Fdk54X8D+aktXkpcP7WErmEgP0BGnXf8jnybt1VToD7O5YXu6/MizWikL+7eMtaUKfRMJX7pjZWsRVpZB7Hb5j1E6qQsI8sgV7GfkUld7Lplzgd8MSQIal6qQNr9smQibw21qrXX/0YiiS1uBEFGM1Q4lYFm/S6TyCmamrQsCDTpudcgrN45V/PFPmLRDB2HQa0b+BbcxFSlVOnpMZ+i9xZI0rW8n6pvC97wfrwTft+iNkfA9Zvll4btpf+4r9vdhVVR/HZdfCV8mY0/9xN0noCXTRmlnV4Q3Mc4zxdbPMu3a0BaWLzO2UMEtzIaOJ5cJP6OxtpGGD0vA8vhOkykYjxs5DrdwAmyTlYd3dnmTfVztgK0MLBODHuv2d7qODhTwKpghifcEvB001N5WgvaBKOwhdmXptBPPvIt51xBN0xmKangHh/s7xaMcmpGtXXOgMfg3x0h1DepPfUO5gWH46aGPDfcvjk+ivzPjEwkFMiXFXj7pXkzO4ouPwfTSSSIHjHBj3jRc9XZIonUB1UWbspwOqkg8rQa9KtQ1aTbYNjF0K2OFWecjl8Hw2X0i/zbOC8tTTPh3TjySh3vUxfEYdn52sDzVi2KiKWe4fMc13ngUcKTB8HQ1tpZTvPHzyePrVDEQqs45g+WnvfGYmBx+YfNcso5xbPbG4YE5ovW2wcmDg3Pid4hbJUYiGI9DMJ6grtHbcp7IJg/0mktGXPZTmGHuxSS+fgRVRrf/SfKWTixyw4L4f2DVLkleEuGVCnKUS4VdHBRDzOkRkCSK6CpyJ3tac1pc7aTA3Xh8OTG8lpin2J/MOiymZkXFnYg454hUT+KnB1d4E4xb/rSPoSd5JdRGdgLbkVBEduIR4pbi0foC1ndhgXBNii67JmiMM861AubbUJHVT/B7btR/YLbw8Q77xK2nDBnXCNBuPhdaHgSNHTSWxwiyB/35X7QmOI0OS0VP2omlzaaBR1WYUqqb4Z7yVvM2qGsBVKyDPe88n+HhaW9nK11s0T94CIEgfVCJOriH/L3l5CHUSB5LzSkpthYN75ejDr4NeNlxqM0omtg/R546OCltC+XST9uSv3QYnZG+UQqouPMXxPXBKigItJJ/Rf181HcUqnxpM+3zypk4mDuAYIFoUPB9YzCMeYGFCRoN9SWTNuMH9G/LZIbAq/8U35UioG9SyO9Bu7CYPjCPP9A/8gNJ3zcGL/t6vwt8oZhV+5Hf/iu/fXXk2weWCJuEy5+unV9qFCquPKoDDcFgUzxZB3Wz/4B+z/z+SvT7m31R9Pv+7/4nfjDwiv11OBPVX+z/1t/xJUIfak+9gFj58qlQfocKXj/RC+1H0/cXLrni/G6IkucmLf6fxjPqiv1taRvV37X/W39xV+7vmqj+tn77P/W34rsrrv/oaP3v8v2hlUNi2WsKuqUiTggpdgVdMKP95TsUWypYkH0slrjgba+JAFBg1FOkqa1c/mHMZuHZY5sRLV3Ak9SysZ70oOwdSUbzhK77Wbu9VV7yNkq8XkzDy/3dSe+MVWLNgsaU+E2BCZKatuAu1jfzlwlXid+AgIOI1IPbAT/ezHdG4pEasGB0nBXe0Rnw9MHNLA4stPEtDfMSrSb2+qS8I7BuY9qQMwV0KT49fp1p9HzJFfDGjMamAVtrvAUW8/ToxDss31SGM1i4AnzrIX5jio0S2SqhrjBWIhs7MlNBMBm66jE5HxdzAvliWkr2CvPSaAvNrd91RmL7RGXMnDQcsX/gbLzZ+S4Lc41sl3S+6lqmR+8sMgySPiu6OY7B6yst/9hLLy1LFBFkSIS1pG9YsN6geOoSZd9pczgfhttIeEpJxr10QRPfG5LJGUWHB+KuQmvlSLqB78kEzES3xGszfEIGUaapTNMyGnpKNV7s57bvcMnDymhqLckj8ikUWWmdSt1iUHjBd5KOtgCmr2l8r5hCR0ZmsYrxaGiZH3ERkPbdN0RHy/dgD9AAvZF2AEes8do+heeJsnf9JbqlTPZ+YXiWqTvC1lM2Yj63hxPBVwuHkXxTKMVyJizi6D1h2AopXjZSvGT1REu0RYSVr1v3RNlP+S1/T+sm9s7L7oilmo1cat+RvXCrm50PCNwLalu/Yr2MsRBddzX2cEd0LcsJ5+8d9NUs3rd47a6vxYHgN22E6zE7dtcCjIxVY/1tX/hdrJe9RH5lPPDLECo5KsxdKZL+fpI1EA7jGA4FAxL75fDPa42+W1n+ha3R70cl80mDJM8Y3BqjSvXhAeeNQUrWLfNVV3f7+aZhl3/xarxwtNolzaGLWJWURkf+ChtzdF9ZCxSs12Wm7Q6NiVzAAMNwWzLVmd1yOV+rS13RjSyTq37+if/LUhd2y6eHc7qNo1OYmd2m0Evzuk3m2+hk74ctQk5HkfRPrXZ5SiSl9ij8UkqOxRr3tKas9RSnOooceOagqNsAZVo9t8WNCQ9dcbhD69zqWiVFVwL3AVltaCdPP9MOe9vkVjfmyM+0XT0HG51RPEerYZ5/eP9GRrXi0eLxRi2QikwlcsrgatAB8g4r9no+ZYQvqQ0KBoRshL7cgb8GXZ4LLZ5NdaXUn3XIUx11+J7lsTkkW3sHMqLUwqfrPEdayt5PCSXrpAZ5yeSgui2jaEU/aoJpFu3nZc90chuc3BiYKEU8a4Rnk56G+kuBiTER9Zew/kGovxiYGBtRfxHr74T6C4GJ5oj6C1h/PdQ3BCZaIuobsL6dvCSj3lPaosjbCathUaXT5RJd5wtSdY026yBltYtH8ttgDuOMgV9pu9F33SQcgil9VzHDL8aOdAwDMd7yW262mmZn4TVZDr5Gz58HQCkr9tMThwEC37GLBf12ypiOTG/VDlI0mfPdScbJS2PkV/DegrOzHZ41UribST+4/Hw7mwu+QheY4ZnxwwgYAYfE99KgepelpGx0qWdhF6VnHWnFOX90/2Ogk6R4iiU+cstxeFbQRWomuWhNO8yOVZb3uxsIm0suaUm0OwKj0AfBGBAFEWD6K7oPwmWfSdewyZ4eWAVssHYXkOyvu+hxDYYdZ8gXwj6DrlGwJLBCiTsvw1Q2fMlMZSMxFe+X9ZjmLoIz/Ize6RH5yNFfAHgK3tD7IgUSWEp28ML/Gb8SMM92+jEv3uThDqLaIPtXMNEnkmAKZSEhvQJTtnzMOUhoNO8uRCvy1HaCD0iyrzNa8InpCNhZHhMBQM3Ap6CB9cxqh8drwxuYJcxnt4OV3BA8OcTd3iA5lHutblJzx8SCPsyjkp8txkEvMgbdqRAG6uWBipuz/Anrt7M41A6ar8uRnzYXklIET7TtxjVjEvU21Uu8OQfEloXYHbQE4WwxT3tRE3iBxXXZW058LmIT8p7gQ8nYiJXTJn1JHNS7PUK4OhobkQ/te17CTF/NZFzO//ByYoTXAviLc4HaJVib+3L4+1Eol5S/ghbHlPsXZYwXs5LBdnrqgnSNrj/BKlagtzK+GIUup39hDC55pu9EbpdqDxekaP4Y1b+CKA2YrKeF/JdhbN7JEfd9OsWlwyH/wyc/E3C9JTJxUT6dC9ZqlxYwNO/Qv2U7hDbgs6bR+PkcRv/NZ8LvyJ9w8zaAnFO1eH/BEP88ukI70+/14t9hVE6SHOpOR8E6PCjIRJqQCGhScBAvtIAHeuv6kH7/QyrtNN8CqZ9tMObFvDBhhQ/ZQW1asbi1mZmjtgTGAvQShYHpuMbaYZyHejKCRdK9RZZmV0G5VU3xlCP/w19N+V/RUOhWc6m/EvvbSuziWboB5jSyxUj2t5OyH64FxoPsb02A2J/Ls6/anVLxx/nnL8v/6vIOu0FI8R5jHu0EiTGlGNlrSoU7cC8wwHpggO6U8rPy1KF1dPXnkTrP0ZbECUcGyOKwzWuezx7dLJNKZ/6/zwDXuqXqciJ6gUFnvWRY1Lp+RseJWNQe+UxIeKtJuBPRhBVawmdI9ya3tpMvYYDvmA30P+YhCfEnfHXLp41BfXmdcX7jd3LC0fSQuJW/IpGR9U5AVlKU0tYxspYglnYWWOqfSXiJFyn1s0YqY4yQic2YNIu0TQlt4nnCr6VIlPTM0Pk7SIni6s9qpXYHqBHlaUF3oEdGWrFrc1VVl9mKtAnvFra47BcmJiMX8Radp9szk1HxRUa5X9w4OtONjDLHt+75DXiBsmc0tMPDPlcg10KRY3Sl4mJBo0H1XWSKnI0qLisHgr2ANL153ayGHof/JFZ1onjV7h+BiBLvaQCKgglsmVMeIa20xmCW2vSPmFZsRs2H7ZGAdg3AL8e3pJAXvRQv8RaqSNo6A7HxAE0wDPXkKkx/qO3+GLNmbMlMK3aLsPu8Nk6hxWWqpRHb0T9/M8aXT98clu5JEP7RzDe+lsGnA46gp66FPH06DeMMEIAYkAXUSs++2NybnQNayF473mN1IEb2Xm/FPN9DzbK3A1bVxcq+IKX+HmplNFXLHOqGHIf8dKUjpUwFqWbCesrRGeg0Pa3Yc/Ri1TWXwX9PsRkx314he5eRf9szJcAPYwCPuxTnHgh0ilUrnQPM02XvUBztYAm1zy4tMbk5VK/MfSEwOMa+dtL9ovhkYHAsFJ2iOCow2AzF/qKYFRhsgeL1onhnYHALKHYRxZsDg1tC0aqWQvFfuUl+S3YlX8RhtYQlT730TDBIlxSHVSfV3DX0+CN8zDSc90RPxag9RMZ7yN9i0F0FsIuZABD6TefRLHhabw1/w/JGNAc1xAt3YKHVKhT0cVnqHjw+GU3+l5lkKkjF2JPCPaYmAmstXlw8JpOkFxY//Ql/3oT+Gzw6lkkpnNaQDFhamddEWhmxiQQPEiRy4OlClj4QNbTkj0iUsG+KECUOxZB8wEKY90H00GLLxO6NZIhhjgsIYvjNb31f8OUbQ+eB6h7Mr/fEB0ZcBsU9qWVKyga3/awMujafcow0rAJuMYMItAY85/zPjMVCXqrqEo6XfNj4Lp54izHesDEs4IZwuPR9HsfPbD15g4XXuI3C5gJbIiwIvMywPVlqI2btUM85/X1mo4tMvrhbC0ZcVtVa2/dedCjkHozvefj9iFDIJPQ9ga5GZqkXQ3DhDswjmHDkDwDmNp+uyWPhCjZh8c+Im0HZO8IszpqvoUtlz4ZkrJlCxgL6XR97OYEqC5NxP3gi0mDjVndFG2xaVRvxEgDb+pjTwWCg0wC8ts/nxiy6xeTHpjGpw7NmT0Mb2dfpQoTBAa/tFgS250hRXiDKaHmDIhmh5vREdUff0UDpD/S9GIxhWfITYaY3BxOH1EvyjMelMIqmFes9T4XuIhI2qSxYAUKTlLVom3LZy93ysB2Xl1ZlLwVzXUZiffAnXlTff9BHoqTRuN77snxU9jZKjH1RfDQxtBNzxE5Af3Nj/hdO2oyJbjyBKt4c2+whGHe/Q/EckyhP0EoO1G1y+3YOXrud28Epf1/qthfLhX/HNK5bXLXVmf55toxMUidxVYYHgKDZy2XPw9BAz4Z/gNvANr9EHkWWD5airLxFGOb6F07CEafj+cd7nBAmPmzBaWvdEN4Yh9/cVS88gbmIhWyvr8Qs92qZnn6a/eURQ6raaeXvCKTcfjwqyOrOeUaQ1crjUS+8YbwwN/qFtqEXptFdALci/VsftvZJEVI0HiXjmT6xeH+PbwBD7+Ru8zpFdLnsHe7yAKUpdqv7CCNCU8YDmcRyczdJv47uSfovOxh3XEAqACjd2g3r3KoeF4UVd730lNBf/3/snXt8VMX1wG8ggYDIRgGNirpKqOGxIeFlCESzJIGNBIgQFImYLLub7Db7YvcuJBIgmgRY40JUQERbo7ZK1fqj1lp8VIMIwVYrolb7s9X47F0jhfoqFYHfOfO4Ozvsbfv59Pdn0SRzv3fuPM7MnTkzc2YuiaYCz4nQ38X4rV8koojnf4Gvxr2v0FcDD7dti8NI7ZpTgh880D56KF7yD7EQ8IthiXfdemAgfclBH4hf9oXocRmdU1UPQ3sCb9nP4Dkymo4PhKzSbcafgYv0KWQ8BJ7ePp7UkGDA/T9NsZ7B7OG+wAKjqw3qKFssY+szZGWgdQ95pSJZBe9pz+wU7OGcNker/JbuPkjHlWNkjVU9RxhV8vmVjA/3kChA7e5/oIvb84wkhiHEyERbeh+ugLxMV0DwfPS2lpyRaabNrfT5lXuo1U4uBNIJaui+tpPQ/l6E7z49UWTasmZ62HWm9tpOZg3S0RPdF1nRVvyXXjJ3cMS04TDdHfq7Xjobktk5a5eWh5tyPEcwE7aBlnfhFoyVOlrptATE2J/B5ov/oj10D50vdlI7HjO144FuZ1pfE/Re1Tup1WjkJkjx0V+TvmJTL5UtiHo8pDn6R1P5ayi3C2yOV9g6SOdTQ4novjV1HIWYUEiQWJYkSMvj4xOJIUZANmplF/dwe7TitF7SFk7DXaOjTyf2jxf/fTVbRNI27qSHkRQJc9alO9kKaHS/0xqFluQFiHtG3LQFRjqnnb0DyedZj8TvYXZqqDOrOdlER0atuTpntLb7HhYEhIibydWc0U5rL5smKV5xANsnN+YIDWNx5yTUkJ9yjXgcaUK/S9KIJ868kp4bQhTi4eCYuRr04R+kMX34XEJAHR6A84TRvdbob+tN/j8UHLaOe4kpxOXRQ7ZY+kZrW9/3qPkobS+lo8WrFUYo7Q8qugKsUAX4Q2ss/ZzoSzOm3q16Yu60Ga+Fa6Kfz4Sr5TH3ALiaT68WxtwD4epqemWNudPhqoBeTYm5M+BqDL0aG3MPgqtR9Or8mHswXA2OajOnblSHgDihbTsNAo9OiN9xirz5Q/kcWM1+eKe/hwagNJaeVg4Drw7cMgCPuE+R9xxVPDpjF88gN/qf+Q22Df1PWp8hbcRR8EcMevq7k+2B3Lo9F7UH0rQdgikQ2nPFyk+2HR+wKmEP9PT2M+yB3NweSNXtgXBNDm1FMrVv76bGP9bogdarLaaOzdhNr08DPbWdvsPFvyKvQmVnYdvJgab2DaSKkD1GD0f4u3sOBFJwGM/MsbH3+i64p30HaXl2AD0Ip+M35G08RfYTYy6gUVK9tpi3/7itc4nSWqRE/LhYvxQbwzoQ3iRuN8eNKb7fRlZbmUFdCT1ih4XYxUO8EMe6seLLI8Tk8Z5teGITP59ODz0ObcfpLrQNirVAcxAb9VcVvb+AtkMaqq/k22B4npF2BW5Zw+Ks7yLxxWfo7+nixFLztXdTUyMslhJoAkenrZuBJnL6NAS+yrdvZ3sZoIHrbS5AC+bXtcHbxFV7ascSfZ00XVr/VvEezW/Bt9DMP3g3XdmOZdT9kq4OR8nZ+Jn9jyevX+ey9escXL9OTDhEf0J6WG3ndqH1/gc59OdxsqZWBjUnx0r24LydRhcCsWtmJfGb0+zkmuw0uhhOLfqbMrWfbSPVE+oSPDzA1PFKGp+uJR9M+24r2skfheF58RUvMbFAJuY9iZlAu/l8/FWCv6qcOHNwWj0fjwikfVVl2vGZo97cC1GaKo9j//ckXdd+SVqm7mwf4FbYurE7PUmNf2oomaHca4tOzZmPTZsNW6PWF+myQHtRGvE9ayzbUVfY+XwRLpLhwdDQWpUR9Y3erUcrriJixUU2zuTDyGDzIiKH0Tm4w63OFgWlsz+NLPTZoqNzbBnK0HTo90b20jOgYulnkaO/iIeKzvZeXAFE+6Q627hDZCwr23fiAUhkX+eiO/lnlnAkM26fqf0QjmTS9ve/R8a9ak4mFXj0rlNEweF6FSmwTlpgqG9hWevdZMudtJuklQOXVY/TZdVcsqzahV22fvDOi3ehEWb8UsF+GG3jo1+i2DreW3dN9BDJHRNFWU4dToBCplLl59Y7WH7uSWP5aR0g5Cd6jAqRCJAJb85pPFaOnIhARNoJF2kHUXxVyQKlslyKu9BO0KkJXk3QojfWTnrLmbmmjuVpwt225wfa6Kx+BzUBOxXE+svk3o7fKBA65CeBs7czerQiul9L2yqch+U9RcZ2bIQKEvLmzHounzau3f+Df0AFRLMQzEUmmX5DEw3ISvL5SiAvsq/3qLaoi8trAJGXOswGsvqAtR96JuZHpw5OWv/g9QKakMAdYs2gNUGuIfHPks6/1eZt0Td4lZxiG7y2gBfxCPwW/FaAmpPbW5YzkWzP/wHIJn4OaW+hIaqLHo3mal/eSc6QG4mfGBKOzyKnVCXe1ljGnU/gG96bjjuyFSIyrE75ejuJ9QfEUbolcV6eqX0UTqiAOPq0ezcnn+/38fdiWom1JJ7hBkl1kqSuuSPpfD9b58gcaFQLbdFDZ9a/2aT+xdecFM53ihX/wg/BvAWlI1SObV1ky3khaW8Oiu1Nx3hat8biUz9Ofqq2i+ztnUperL30IIxhOfBiXYZJSgQRw6MUqnPy47fr6zwksSThQoLx/WjT0kiiD1DrBlpJettpTce+bWRyedfE9PJu5Rv67j/xL8p7OiQ8fi346tIuSjxfcpI9X3vG83VlWBJ6IXy75RT9uGkXZiF+oWjfWbzCBz7ULUmSmraFrAEs8pEmO19bknz7PHp7r5fcnqpNT779SOwUbUmiL+GXY+6HippSfrzAbzshpqcRQtU+2ZwU4k83J0oOQ4keIF9Rewn7HOwk8vE4ive/O336DPu3LUb2aisiyfZvt/979m+bDfc/PZFs/5Y6vCVEp0QtJ5ts49AaNyeUTwtoOelp62d2FlsfY/sT6EQAbs8g2svPO5lKNqngCCqmF9NYsqNazfJ99By3pkzenQRjeMhE/6/JuXoZXz5DPkLZq/3xNtArj3QWascg6spYxoZGRXnmxCjyjfVYI07e4aFFEx4hJqPOFXy25UmIqr/zDPvHmJE87nw02f6x08gecAfbizERVXI31dKWxPipQxjwCNTTg6A+TWw7mbH+ElTBg6gTZ2sXd2L3it2OG/pUDGkfDqSbQKK6Uv4U++wen3V5nn5sClWrBbfLBwCM1Iooy+YsPUe7giIzQ9boy9pIinITT6Zryu2kkuK0MZ6r03ZykKmjd0Dy9+Oxb+3oaT6vfzJbH54X5d/VoCdkZD2bxnehah/cpp8Xeh3cpQex4kZ/8DeS9lzac8zPeeoU7LSuxk6rTzz/bhNvr39LjpQ6QYrvRJapfSAEuYcEOe5dcrzWl2zTQBVo2APoxlVi46FtvJ0ObJd2zsrBbQgxfI/x4FL8fAw5NeHTKOs897PqWkJGXmd1aY2b6JQWVo50fd9NifbxJjZTlsgVO6+VnbPxEvMwinRAOFsu9sfaCD1fr5I28KFTchtowzYU01JJ2sAvQVD93ZCLkZK3pH3Tr4Kv+I8grBex+dbm30a/7VgFOS84jJtx1nSy4VcBOTbTi9UaZ8zJp9sf4i8rPa0C5x0m3JiTuQfDYqei9ptouS/eSOUShpBJp3tKO7aJbuHCfUtqTSUenrBP/x7cGOY/j0voL1r3Riqhj9ULQEYgHUjD+r5k+4XKNC9uAsEEzrgRj/iiB2Se1n65ATK66BSdQQniPE4TtW4iLwn7tDMqLfiyxDfjBHvnGr5zSRsVJf1vVnziyX9h/x01ah8GdCe1DyiPf9pe0m2j2sxoor20Qns5LG2dG/fq1oOMFvaQVemZOAYdtc4JwyQzW9RswQ93aKc3kJeWHLqbpT1AthZ9oP1xA4m5kLSh2nMdUK8KtbeipIfbWY8q0QFo/t4ETqcTfpeU30RWH9iUGK9W0fFqhTxeBSXxfyGjz5pwFWxIOq4rQtgbN7FBLM4pRl83bd2nlW0Qh6klifHrhKQb4n5aLz37OFvL3kRPssWEDEYRDVifS4sF9Lr+Dtpiou8U++9wPiNXmM/IJ+3kDzaSrY8/ceE0E2jU5Vlkg8sBzbeBTvOp18PtLhcxFtGWcrgC4AYGSzn0AVzLYB6DkSZcedvdgc0MxE8+mBhfADW1Czg99/nN9qSbBWy+Au5DdXw6+ebIxPd/8Hl8W7W7kr387RTf34NWLF85yczG0bYkPwfJIWdf5OryJR+iztL2bNDla2q/l36OdxiM6rsGUvmBYEsymYBGt9HqigMcUH2Ub0tyQXObnkFO/oKoR93upFNMA9vxiJgX2IwT3Ghx4n6YNkIH6DSI9B1KB+q0EeleStN1Wov0MUozdFqDdBulg3S6EOl6SgfrdA5SD6WZOi1GupjSITotRFpM6VCdTkV6BaVn6TQf6TmUDtPpWKQnbiX0bJ1ehPRTSofr9AKkr1Nq0qkJ6TOUZuk0A+lDlJ6j0+MOoDFKz9XpEaSrKR2h0w+R2ikdqdN3kM6jdJROX0U6jdLzdLoP6aWUnq/TZ5EOoTRbp79C+tUthF6g018g/TOlF+r0p0h7Kb1IpzuR/oLS0TrdjPReSi/WaTvSDkov0ekapAFKL9VpBOkNlJp16kFaSullOq1HaqH0cp3ehPR8SsfodCnSNEpzdLoYaX8roWN1Oh/p2630TTXjhN9R7bxbeKOWzTfY5+7j8/7j7fBAWStpz69AdyF1j0X3ROomfszUnYvukdSdh+5M6p6I7u/XE7cF3cfWJ/x8Qt1T0P0udc9A96vUfTW6e6j7KnQ/Jbh3UfccdN8nuLsEdzt1l6K7ibpno9tL3SXorhPc1UK8NoHPom4ruvOF8HOouxLd2dR9DbqHUXcFuhXqnovur9cl3Bp129D9p3WJcA6tS4TzMnVfi+491L0Y3Y9T9/Xo7qbuG9G9lbrr0L0J3PERbJ8m9BpYfvi3ar3etnY8QfamQYWQ5vfo2uC7+ndJ+H5usn8+Hxv1Qrof+ONWXa8wteNGRahM6WSydlAaVRQztUvX0y8xvEMPjhv2rKJkKS/gafvQebzUSk5VG/ZCJr1+Eq6fQcWPvinQtNTgAIzoIqaFB8FHcN0pYqmj4lC4uKsO7YkhBpzkbb+PDnQzsTmoIQceHGHhwOPa9HWiIvPuU6fwKL9hurYz6tYa7nMY9ZlFfT7xFFV5PlvL1zPyyQZhtkUd9cznWqj+Q+t8f62u/7Rw/ecF2m+quGG9lPdzU1v46flqC/Zxqh9Tn0gySVb/Mjw/bS05Lx+HEdXAv9WGrJWTv28ZT/78JM+kdwQ97p0W+vaXJNYzsD6Y19F6UbhWP8m/Y9Vpdt7c4rW0eLRr1vKHLadJ/55YDyrE+lBC68Ob6xJ65oVklQc/vTra2nYqff14suqhrw7taOHSLERplrDVIfa9WBjY6PqUEw8MIotEoFS9sTZp8Akp1l6gKFs/Kc4a3W96ejBaVuF3NPCzAYlhqFbSQlYaIEkZ9BwTHJDiNs8bMf1wM1E/y6JHhTPrMqE8R0D+hFWEp1rolM38jk/UAiv96nofP8C+YpzGloSO3MzGebjdRc2EMUfljE9Db6Ea33FYzcR51M/XYB6m5tBJ0SPasha6S9VGdpIJ60VoztI1yxIZSlbGyDonPzSwfg2d5jC1DyE2WGiZhKtK8ZP6911H3Iz1FIYWsbnftx0fvfo8W+zsD+y4XJx+iy3t4Ok+ZsdMz6XswK8saafXkkpdvFxRWOFhzf5Hs5Bg7bE1ycltoVtgl8bPxY0FXfSQUHz/4gNOk/nXFtCX9QElTrslpu3WQ9bxdHdh/i+pSPD8kJakYrCsIVMI7PtkpDhMHT40/vkZbf9ssYy0e5I2L+Lq3Wd6+4bHZpPzqh03s+2wnUXs2zet4nkWw8jhE3S8oK0Rjt5BOwJbW/Fjj5DFm7Pp1Wv06jQ/beTZUjI4tAzaxpaiyGEhINrlVWiFMB/6W6yb4CC2bGysXfyHGjzPht+ZLdzxwXNaFjY9Z895hJqLPprGDicpeK+84BM8T6wlpwTegP4rsf2Z3Zm+p6JzrXLtoujesuh32GxMC2Lkbb1p2mDIe9nM4u8fVpSly8Je2y37iEVDZ8agRzDZ7dmt5fj39uxN5cQQLLuL/L09ewf5m/Hrh3Hg/FpF2lto7rqVxFPwyqL+7fVdbGHn79pDTfxMn0I+jrKR9RwpZ1MwZ9PX0DU6W8cRdS2W6aafsHMMvqwwjX/5S9MNGffWksO1mvy4j/1Lm2n8a1+abtpLxmnkxA1MRGX0I8jmuCpcbCDmL9rFzUyYpUKUJRjlvptpPc4lxjDxitP8Ow88QPyQDY4rtbZP0zBO2xuabYiGMR/80rT0lfhasj6L9kbRj0ja39DaPkqzDTmEXnrAS0+8LFGvkvONexdjxYUL8TyXm2nWycdc67vI15XYfB8ume5in6fBqTuttllfOlWHgFAntp0YuN6ir6Xlr+ZraeSpTvoU+QgP3aJYRldVuxMLSTj7t4fN/u1ms389fPavCopwfif2vtH9FeTgebLF+ES6ehkuy5lbr1ZMHRPwCPYTGepwRLkEWfEj7C/iO08niXKbEmO8AhhSAR2gaOc28dkcU3vJIHIWzqb30/henugEMhdGTBZsvQoG1ltCXnsyJVdfFi1Nx2NIiTRxLy42WC/SJmbWiPpoy4j0it6yDPKgFRyZA1m9fEylti1zSC8MXbQt09bxinqlrdOaVdkZzKqccUwdL+6PWpeJpysMITn7PTkLdBV6inzK7Pax87yOBWolgc7kgU4WAx17y0k8O0S9ODnIETzImSuzIp90QYuU3nE4MhwalZ6HSKOCZxVVvPje1KffufX9i0rh7bM/pCR/40at7Jy29SHy8Xi1GGtOFRGE1qVif3/c9ndnzlKbpzKnCk9Btu39/FxbLP0c/DhW23Bc8Rx3oAx3hpxyrMp41olScnxDPjX3rfbBKtTn1E5TdD6u3PeE6VRs++rT9ATSLWGM4Ki2MUzX9bqZRd1uNkW2h02RYY2KL8E2uIsfHfsberZmwWEsvCh+lhz1yfgy3n9VOk7q/X5lTtaCWPqJir1/SW/bn0YPbngqwmyJnsERYBvWhNLesmKyaFdvjdrSyQcLrFEowEEo3nnRsmIFZWzqULG72MrnNxwn9fmnypxsKZ4srZLFk0VHmrgJnEQGIUM0wXQInsSbptBiJPFgsVfMOGBqfx/yTIvd1PEkHu/72kmWv4roBwU9HUfWm+NXDhCP8MUtE9BGZ5LHR8Mt67dzB12ganjoZUXMm6F0lqMpByTBatp6AK2ctvZYM8Fv0QDUJqydV+vz4/nai2H2YYgP8Yi4p8ty8mcNNbV/AhfRv8aWpG0qm1rVdvIqIPjCvd3/EvafvRnlD1BbbWIkry4hTWZkCY7/VKIdF7ynbV9JC37zyn+j4O0nhO+lcN3s6zB5+zt61o83tT+Ph1b2ZrzKdhXGHz9xmi9uab8L4yH8vfFf0LM6ed1+CmPeo78VWMXLQMdMquVpb5DV+YwmCDe+9AT5PPkWtshATlF1sJFL1QtFGOahlewTFnhKDSiW7fjZhQOJNJegOGNr08Q1jYlhoksTWdVUE1lVVOP4LwRtcRxDyycqe9ZCNtuq7VzJRzX5OFBGz70houGnJ7x/uIB7b0zynoned4D3ePgU28aAKH4DXKnnaJcE2RtKtmhDErUDZelV2LR2ZKIR2OHy9m8jg7FKZakvw7MN8+FZ/NQaWVgD3cm3mB4Wh39MZccgxjWLyQa2nBCW9PzEjPGoSVX8gyEHgzyJVfBADTwQx28nRT+Pvh1vPMmSuZSEXDxxMc7PEUGDd7KvajyilwHF7z+ZKPc3VxLBxh9k5rL/tIr94zhpkOIh+lGd1PPPl4US889uOv9sT5p/Ts+Bql1DqvSwHLSXapoDIgltpupkZzYoWMPwA197mBdcZ7wUx0yQjej78Oz6EL1BVPOt+/oHM30Iba7uChidv7VUH2+L46vwysT4Ciep09PXj8E2d17gjMHU0qT5aWk8RXryDUE6lII3jtjbPazb292nW9ZljIsxmzsz8fNj3c9WahhxQ4wJIlccZE0IkgWMgp5yUM7OKpthefg+3POycD85YKNzVON95HiOHH64WxadKIbR0FnRnrLOibfCc80ViRFFwZH4KGG/KI+m3aef8Yapa19xOlFV3D5aVVzAfpNNDDacOVlc3/m8kn6o5U4fXQ062zZuv7oFP3D4Me4n7fcm22uETsvrZJk4aMmEPAwjg5bfQgH075LPvxtG9H46XtgTEI4azKfH0Lbcy7R1yOMwshaGxqlk/mRIGjvfjuXnQBsaRqSRgot5sfspvoo83Ya9jLV3I5rJEHshnAh5lo8uYuUnK2LLyVlrhfNj6v5spp/MpI3bV97E5/tAAcN2rbzzETMZVNra9mWCcI+TBFTs/SRdG+VNaurmRdtn5RIjneJf7tQf1I42QkbBO97Op7e37sR9BSSJ0JNZo8RVMeN99axiPGLftIGsr1G9W6VVmKrbBe/1n03syAAwjfaodpP3jMMQ2TwMJhl3HXVchKd+PlEvlAeeDLrtHv49zMYAGdOW6WAZBV/t4KCCggd1UEjBtTq4ggJFB+dR8D93c5BBwU06+NpPwNk6+JiC57dzcJiCRh3speBCHeym4BU+iNTup6BJB5spuEIHayn4w1YOvBR06KCGgqk6uIaCj+/iYAYFd+oglwKrDs6n4NidHAyi4H4dfOMjYIEOPqHg5B0cvEnB4zp4iYIaHfyCgqE66KbgmS4OtlDg1sE6Cs7XgY+CA1s4uJGCiA7mUZCjgyIK3tzMwTgKbtVBNgUFOhhMQV+Mg2/J61O8RQefevEAaKi+mftwj/Ul35F6Si//+++///7777///vsP/sEwSVnKjhrD6Z7Wra226qzsc3Zmfm3e1D0kcIty5zJFaVeGt96SeU7m9gr+HD5zA/wsk8KrYX9vZH+Xw89N8FObIm7c5mqHnxUp7jkFtwt+GpjbAz8/FO41wo9XuPaxv374CcBPEH5WSmGH4CfM3GjcHxHurWJ/V8NPE3PfDD9r/g1ZtrC/a+FnHfysl+6fPtS+bcm+c/96ffNbqxp++bMP9j337LhLnc+Y9jZeal5bZnpsbfPmSdvuaGwe/vxHpd9ctH/RN3ffU75BmZC1b/XPnx7W1PHmV4V51zZbt4S++snW9nuu/+z612/528zFFz+65ZZ7F50/5qOdjVfMPbjx+t6ml++f/MQHbyz8+qq1S6Y/umbMo8Pmrfn91edf8saP+v528fQf/fr3268/ar585c/f+rHlNu3HUy5avXDJVQ8/Mkbd/sU/y9uuAYpybgr+fRouIJz5Dz/FmMp/dGBqvtqATzMIZ4mSmvsM0nmPAce0m1Nw3LOVKl/rDeJ9wSCdtQb5usGA5xvwuwzSv90g3nsMwulVUudrh0G+yg3C+cYg3ssM/K8amDre/Qbh3G+QnskG5fJ7g3AyDNLTZeA/14B/bMD/1yCdNxtwh0E5/t6A32EQzq8N0tNikF+zAV9jIM8ag/T8zSA9aQbv0dFBinJOCn6VQXrWGqRnlIH/Dw3S02uQ/gcM+DUG8Y4wkPNQA/8vGqRHNYj3QYN81RuE4zR4j8IG/i0G6b/WIN7dBuHkGtUrg/AbDcJpMwjnrwbyOWJQf9428H+nAT9pwD8z4BMN6rNqkN/FBvzPRu+1gRzmwM/lqdJvIM8/GtSHbw3ivcSg3r5tkP49BvF2DkhdLo+T8rpA6csdQPsz3p9mMD4hmVuY/7rxyfwy7t+SzLcx/+Zxyfy5dMYnJfMniJzTlZIddBLvQXpbGc7CN+cl+/90IOXdBcn8ZRZvt5SvJTy/UnoKWPjdUvqH83RK4Tdz/xOTeQXzX5efzBu4fCT/K5n/PkkOg3g6JTk/yMOX/MdY+HVS+B9zLpXjazxeSZ4PcDlL4Zzg8Ur+v+H+pfBfYeXSJ8ntAl4uUr7e4/VKKq/DXM5S+K3cv1SOfSyd3VI6o5xLcqvn6ZHC+Zalv05KfzXPr1RPLuXylMq9kMcr8VJeLlI4Zfx9keSznNdDKRyltrbBF/DXhlV7SK2tVWorqufXOl0hV4MnrLpC1fNLvQG/q9q+wuui91LfqXU02WvrPX6713MzXrpCIX+g1htw2FVPwK8EA16vEm4OOwL+eiUQdPmnT1VCLrsTfHrCAcfkKRB/SA1E0JcacviC+Mfr8kv34XYQH4OnI2GvyxXEQLwQi7LC43fW2kMhe3Oty+vyufyq4nP5HO6QHIIS9jS4fEG1OexS0W13OpkrGAo4fPZwIyQ27GmqDQftq/1BZbXdowY9TiXoCbqUeodf9ULkgg/ItNdVa3dgNsO1Hr9HNb4LcTkjwcn/1IPDGwi7jH04XZCNQDOmF2SthINej8OlhP3BkMev1mOeMTdQHGpz0FW7AktACTvcLmctcHt9PSawmcgYRFOPQltlD3lIGQoilFgYBJhgPnujq9bvWi37bXCpKGOPvwGYN+Ii5Q2lo/gaob74glhofq/H36j4In6fPQhXK5ISEFah3kGqVoc8Kl6F/FgRfLSA5YqirIh4vKrHjzUtEFJ8ECBE4KCeXaugAtQ7MQx6ux6qtwr3IUkef30Ab8D/ijfscjXiY4FgM5VzyO5vgLhdfidewq36hGSJzKB8HI21kFfV43OROhZsVupJtHYVHwDkC6xyKSvDgRDUhYgaphLj6bWHGlYpTfUhl0txevFVgD/hZh/8pkl1emkVCLsjqjOw2q/Uq6GInwUOhRgJ6kHVB0KNcK8WZa4QwYMUUEARh6pAXeIe6T1Xk8vBbwqA1KAkjkJMAp4wrYpYSsk3oDYlAVY9kxhUAr/fFUpi/ojPDk83gHcpQCekKkTvn/FAqpAcXrvHl0RWg1TO8OSy+0Fw+DJLt1IkgpTm6iRkhzIXrwMhpxwFVqGkbJM3NAmR6pYyv0nRu1R4YUOpkhR0N4eTOFS2emetA1pBNblkwi4pbtJ0JRFs0ZKfObMqrHKFwh7SO8hFAe9TclK8HkmM2OYngRC8ltDHBCIqvBVniPeMuuQKO0KYZ8mvM+ILQlDhiE/OsZoK21fAa8gJ9Ev+VZ4QdEhezwpHXjiQN12ZW1kxu7TWOruidu6CJZNrqysXMzQ5b8oU3Xml7ppcqDsLpiW8JuDUBMxLuCcnQijITzgTVAhLeErE5Mtb2HsPBP12oP4fpRnEPUhnA5XBuos+k0muhwhP0nAU3R+uRZ8Fvun1MHaH3z1bem6gMpz8Nun+0nW/GA660/6f/8N5B5Py90GJMc2Y4eem41XaYMp+ecd2/O6BMpJdn+/xnA1auHIpu95E7p+tjGPX28j1MGUqux5B/J+lXM2ut5L7Q5UKdq1e4BmigBSr2fVGcj9TqWPXXeR6sNLIru8m14OUVex6FAk/Q7mFXT9F7qcrnew6ciGGP1DZzq73kPsDlAcHs3msi6n+lsnyX8IcOyS++2L6t1viQcZ3SZxft45J5sf+RMdRmyR+12eUd0u8/C+U75J41p8p75H4Mub/oMSDjPdJPMq4JvFCFr6Sk8zvZf4zJf4E42aJ72U8V+LvMF4i8aOM2yTuZumpk/hx5t8t8cEa5a0SP5/xTRK/gstf4hOZ/10S38HlL/ES5v+gxHuY/z6JVzL/msSXMq6MlcqR8UyJr2XcLPG7GM+V+I8ZL5H4zxm3SfxZxuskfphxt8Rf/ZTJX+IfcflL/EXmv1viR7n8Jf4k898j8e+5/CV+jMtf4ulxJn+Jj2Bc+UEyz2E8U+LTGDdL/BrGcyWe/T6Tv8RvYP5tEncwXifxmxl3S7yEhd8q8Sjzv0niLi5/id/N/O+S+LVc/hJ/mPk/KPFfMd4n8d9x+Uv8HS7/K5K5xuUv8TqWX7PE0z5n8pf4Di5/iWcz/zaJ9zD/dRKfyvy7Jb6Q8VaJexnfJPH+T5j8Jd7M/O+S+DbGeyR+nKXzoMQfYf775Hwxrknc/AGTf24ytzGeKfEg42aJdzOeK/FDjJdI/E9c/hJX+pj8c1P3m26Jl8yhvEnivD9uNQinW+JtjO+S+O7tlO+R88vC78lN3V/3STzEwtckfqyc8uMS5/29Mi51/26W+AoWfq7Ej22lvFDiXD8oGZdaH6iTeDWXv8TNASZ/iXN9onVcav2hW+JWLn+JV7H075HjZeH3jEutb/RJ/EoufzmdMSZ/iXN9RRmfWj8xS/xr3v5IfPd6Jn+Jc/2mZHxqfaZufGq9xS3x1tuY/GXO5W8QTrfEL+Tyl7hSyuQvca4/9YxPrS/1SXw4l7/EuzYy+Uuc61vKhNT6lVni6bz+S7y1g8lf4lw/K5mQWh+rk/g/WD/olnjVOiZ/iXN9rnVCav2tW+JHWfi7JH5oLZO/xLn+1zMhtb7XJ/E/s/A1ieez8I9LnOuLysTU+qF5Ymo9MFfifS1M/hLn+mWJQTh1E1PrjW6JZzUz+Uuc66OtBuF0T0ytZ+6SeE8Tk7/Euf7aYxBOn8Qf4fKX0+lj8pfj5fK3pNZvzRK/l8tf4gpLf6HEuX5cYkmtD9dJ/A4uf4nvXs3kL8fL9LxWS2r9uVviG7j8JV7Hwt8jca5/91hS69t9El/L5S/xHtZ/HZc419eVvNT6uVniK7n8Jb57NpO/xLl+X5KXWp+vy0utt7slHmThN0mcjwdaDcLpzkut5++Sw/Ew+Uucjx96DMLpk3g5l7/Es37I5C9xPt5QJqUeX5glXsTlL3HlWiZ/ifPxScmk1OOROonncvlLfHcVk78cL9OzWyelHr90S/w8Ln/ZPwt/j8T5+KdnUurxTp/EM7j8JZ7Fwj8ucT5eUvJTj4/MEj/OxjW5sv+FTP4S5+OrkvzU46m6/NTjJrfEW1n4TTLn8jcIp1viHzK+S+L5LPw9Eufjt5781OO1Pom/zsLXJN63gMlflhuXf0Hq8Z1Z4vu5/CUerGDylzgfH5YUpB4P1kn8KS5/2T8Lv0nifDzZWpB6/Ngt8Ue5/CV+yMbkL8fLwu8pSD3e7JP4A1z+Et89l8lf4ny8SgwpU4xPd19KOZ7ENlS0AxK4ReA9As8T+EGBzxP4IYFXCfxdgV8v8E2XU57Dxc/bA4l38Xlribfy9Euc5/ugxIM8PRJP5/M3Eq/k7YTE3TyeMcm8hPfnErfx/Ek8m49fJc7/2SSu23aZKR/MbDP5v0yBDxB4lsAHCjxb4Omi3Z/AM0Q7QYEPEni+wAcLvFDgmQIvEfgQMb8CP0vgVQIfJvClAj9b4HUCHy5wt8BNAg8KXLSfaxK4aA/XKnDRfm6TwEcIvEvgIwW+Q+CjBN4t8PMEvkvg54t2nQLPFt9rgV8gvtcCv1B8rwV+kfheC3y0+F4L/GKB9wn8EoFrAr9U4McELtplHhf4ZeKLcVmCi/aUmQIfI9Z/gYvvWLbAx4r1X+A/EOu/wK8Q67/Ac8X6L/BxYv0X+Hix/gt8glj/BT5RrP8CnyTWf4Hni/Vf4AVi/Rf4ZLH+C3yKWP8FPlWs/wKfJtZ/gU8X67/ArxTrv8ALxfov8Bli/Rd4kVj/BT5TrP8CnyXWf4EXi/Vf4FeJ9V/gV4v1X+AlYv0XuFWs/wKfLdZ/gZeK9f/yBC8T67/Ay8X6L/C5Yv0XuE2s/wKvEOu/wK8R67/AK8X6L/D5Yv0X+AKx/gt8oVj/BS7qFUsFfq1Y/wW+SKz/Al8s1n+BV4v1X+BLxPov8OsEPincHJ7kdK3yOFxhdKsu3yRHMII/+ZMcdofbNYkYAU2ZFEbLyeTn6sOTHA2hQCQ4yefyBULN7E+e1+PzqLUef+2KZtUV/tf+I2F7gyuFfyld/oDTRX6NdWL60KJHYTZmRWa0vQqoZocbLeTMFgv6C5tXe1R3IALY7vV6/A1m0QrMXO8JhdV/IodEfJFJTojM7nfoEtDjpfZ/5nq7x+tymp2RkB4NMbbU/TGbPzMxhvIE/PyJ3DllZiIvM9xAS8irxyWFb/CclA5zTVn57CVzl5vn0FDVgDno8ZuZ/ZZ5LCXu5rAZ8wPXXJees3DRvEVLFtQuKl+8ZH557eLqsoVLqmtn31Bdvrh4rNcb4f4KpucV5BWYJ+dPnp4/rWCaOXcRxGKzq2Z6wzKZdRaWhVPMlnqvGii2RyBKS70/YEGrS4dqsXs99jBKh0KXz+5XPQ6Lx6+6QmhQSnJnqQ+ALCz1IbvPZQkGyE36gM+uui3Ebheu1ZDLZfEGAkGLx5d8uQoqAgmnqqLUbLneO9GysID+tdjDFr/L5YSEk+vZ4WbfioDX4zCLcixftGjhouVFZmr8yKRdZB4bHpos74Q/COYMb9wfL5bridGfGRJGbEuDkAYsDQ/US14iE81OV709ggaRDVha3kADuZ0/NEV4Y8NFY0l0csxDi//TfzQD/0/BKAtI5iLm3CqsfGMj4yCl3ojZHkb7Q5BCC7lE22ZXOKxfV5jDasDrYlfEDUURCvjMPhcN2PKf/mPpqw6oIOPSUCActiwOOBpdqrk6hIbIDppQhzvibwybc8fmFdSPHTtOH4L+5/KhQVWHPA0NUDMavIEVkBCXzxVqcPkdzWZiGKjItoPmWe5AyHNzwH+VueaHdnjSmZeXh3uaJZNE8yysVVeZZ3mcTfDb4Vfhd6PH6w0zZUA3gTTPYmbcTvCBFqxoNw1ONFMlTsE/M7c011jUFkugxeJrsTS0WOpbLPblXC6CpaZ5VsUCCAjaE/w9Zw78riwHUkMMiJcL/onhqXnWnDLuseZ6W/mC0vLl5prrrIuW6/6IWSvzVzVnaQsxLwXfET+543IuF81RwU9FVTl4nVNRCX9qnKHm5Wda65pnsVCIxGo9RAwJiZBu5CrlTPPfM59L5EcwH4YS8BNf0AsJAZpr9BSz5T+3y9Fo9tSb0a7b7AmbV3j89lCzORAyu+1hc9jtWgEdm5KwgDbPIsHBiwG/nS7oQjDhAfhV74ekLMYs8EDsfqeZlQk0LB4VwlOdHr+eXsHSOilYhw+law81hFktA53Cq4bslno75AyfipBGO1APF9BQ+6EGkyg9rrBYH9BnyvSeGQE3E0/yTiz5sQTxseUKtaAOK1RbSKlZ5PnsTQZ3HJFQCPdf8J4P/paW186xVlbOtpbOU1AJmBR2+/T7SxaX19qWzC2vrpytTFJ9QaX8ujlltYsqFsytLbNWW4VL+ClfXG1AyxfO0YMkjbiihiIuuV0vJ0bs0DuDAgOVCDq9YLH+2IIl82sXLCwrX0y2E2CTD96YMIoTznzBDQE04SUoP66w7sjXXfw+EaXuyNddieehV0YHbiuAqozOBuh0nc3gcDXZoXsn4cEVu0trGOphupMUX7HCdLNiZayTZx+NrhUiLXxla0utVdbSiuobFGiBKSYKSe1861IlSdIV11UsXrhImYT9B5Yv2Twx3+WzroJeESVZBJEUjUU1Rm8jlLHhvLER+J86FGgWZC3ItnBRxbKFC5gCJN28xjp3bnlZca5yOd4uwl+Xm5VVU/Im5xVA3nBHSX5+0eTpRQX5ynx7s3nydKI1KZUef6RJaSqcbpk+1bJqMiSo0Y/7J66jjWqRmXThs3FLBLjxioCFi8mVmd62hhzuIv2qNOALQnMRor3/HK+9IVzE780FjdJmD7vpPS7nSNj1f+xdfXBc1XV/e9/uar1rP8RHXBXcsCWqIxMjRABXgJNoJe2XtJJW0lqW7SiSrA9LQZaEvBjhGtdkzQLpSnaocRTGEId6DJMaxk3BZSgpmpFnhzbSyu24QDrM1O14GHdKUmcKDu109vbc+87Zffukp830n3Y6ujNvf++9c8/9OvfzvXd/290Xn9RLcXu4XmnzRyM79EtRtbrFLXkBda0xHIm0Y/n7YnUhEHYaSiPWtqM7Em4Kx9ByLWCLZn+9Mjzap/QP9Cntfn9jd7s/pp/4m+vBnCP98sdtDLU90hLDaJp8DWBO/TTcDKfQiFra6v1tsl4ocudNxSBMlTbu7x3Z7K3epBj3mFT25S6HR2EQVIzbDwwTpdzele7H8qcThtPHFH2PC5rI2zcGDW5U16UOKt+zLelD85300v0p+Y0pBTtSCraiLBlElo4+S8cxw3YT4z6T5TaYGHeWGAfM3GYHw2ib3z1i3DZiGLYL0lawQ2TJ1pCle0Lym0EMu0Dy2z+Ms4mCGYh5p0d+OrPMVo7CPRzmmdKSXRvmKZdhn4bcZWesSEu7rO66bW247c3oEZqTzxvzR/xNotl4K+pC25ob22E62V7nE+OBLxZStkPLgpquX8TCTX6YOSnRlkik29/hb4ZmFPVtb9Zv+NqC9+TOvqrE2nzRbjF4hYPQaPxK+4BYCMOEQi6gvKKIBpR6yOLSu+bce3fJfr9LqR+QazIxYdALS2l/fLTPqxcpjPiDYiNfQcnKIVtpk0XvHe+diA/DdMBoggKr6L6jYgYaqN8HvSPMKEbGevtFI9mX37KDM8Co2OXmlaUYlxso49Brtw/BJE/sIeuHZUEcVOO9MO+RRS/P6/SGn69J0nxbfW1tB9vqxSQTAg6I6Vbf2Cg0QmMdxEmmmJ9AaUI+ZK3NV1cppwgMsoIeZyskHbJI6zxsZDITAWwi8iKMjaddzIIhpHbZxmjlb2x3erQ7BybG7hJN0mtsw/IGzrZh4g2G0KfLaAEfTC9390KsOaNhHkUXC0pKBNebmExMBMZQp3cgXuxAcDlbUG56f+PdBd3/Qej+u0AH+iJjnLJzQoO2PSqWwsODw7Dmk4VA3ZgQyBty5UVPMPK342PQzDGpmDhjWCMDe3ph9VTQKeZm+nKxQJN7UcX150Byf2IYavCw3B4sr+WTI5HBweE9+T7buysQ8QXbu5b26xA41CS0Tax30lvnjY48umd41OunabISELNmGIEn7gI1qKQwigilfGUXz6Fw+nk3jmRixknnlZ2dnTdo69Z63GtcJU6HXWU2hfAwuu+9yHnVS8sfx+A4/JK1/Dc5zPonIL78U8EdNX9fkeW//FKWCxTHu3Ds3KTfMx/jm5bKSL9xU16/0UJfHK+ZZLdvKsSVDorLePzcoLdmk36sFMZ/Vix///5N+iHS//1NK+tfMYRB5+L+GtS30n0Xy2du01J9gZvvzPL1cJTcubz+r0CvFmShjVn+zh354wG41jaKP6XN8nmUHQSchuv+zVn+Azi0O/LHAbwWMnH+6mb93OjHfHwG4dluUx8KMf05vv0LoAPnsVuzPHWzoly6GxCuj1Rl+SnA++7J8k8A44C3qIpy+qtZHgG8cC+kDTB2f5a/Ja63ZPmngPUPQf7t4P9rWf4M4PGvZ/mHgJd8WX6fA+T1WS64DuzBLD8LeKUBwnXC/aYs7wS80JLl58R1a5ZfAjzSnuWfA5YLuuMSCPepLJ8FfOPZLC91QThzkF6BHNIJWH4351vXQLz3c54CjFdz/hFgrJHzmBuuAYcAy9s4fwvwSIxzlwfiBawAvGUb5yFAeyfnxwFjgG8I+Q7OrwJe2cn55rVQLrs4jwAeARwB/LQH2uM6SHcv517A44A1gJcAewDLd0MbBowDngK8ADgLeEsf55eF/z/g/FMN/B3kvOwGuP5DCB/wvidBD/AS4FnA+LOcfw54AbCsFPS/y3k14CXAfsDyP+L8COCn05xfAKw/yvkVwCuApTcqSv8xKB/AC98Df4DHvw/5Azz9A0iHuD4J5XAThPtDyD9g/xnQB7S/wrkd6seFV6H/AYz9mPPxm/PvqG0H2hTbZKnttrUlLsGpVY7vf2duyvIq8WGAVhrQyhpu8DzmOqx849aH7ry3/A76TqFefqcJ9dfwDYTgFfwI7r0sbtRqpVPMr5Wl1HrNm7TXaxUJR1CrYYNurQLu+LQy8FGruRo9IAoZbujpOC2/Q4R+QX6Ir5UmWZ1WllCDmnePVgbXPvAo3k3Oi3jB31fEhxLDWlVHUo2mWChh//acf74rrbn8WlXCnlRTbGhunu1Ii/DFO1bxZxhRaDfr5d9gaNF2t+YKe6IJxp52z4U9u9xzIdD1xNxzMY94R3mfTXwXluVP6/6r/NNqS8LOmkGtwdNwlO1drJdxtWuuJq3qKGPPuheDHv39pqDGPw5tcUzX9fqTahPoRqcZa880yRC2y+iHNBeUxDTblnl4mvkzIn9nQec9aL8HxAcc6qhN87IJzcWmNe9ugH/SvBHNtQNuHtJcUc3bJ7In7SA+LSr9/SyXn9RCwU4zMOWUWqt5U/ZGrSLp8EG5OOu1czY1aXNrVT6twqd5a8kIIQ+Lwd1A4V3IkHj/VwNhXqnOcsmtDZKjDHxMi7Cn7H6tIiXCTjp9WnWiJKhdPGxnXW6t2ifjqDWE5vdgWo9BeG88kOX3qLJ8eoYSJS1JZ8rRMmWPTKsRKMyn5vxp/7x/wZ/xL4bdIiE7NVdA60mUCH9T9mkVPF1yg68g+hKBi7os+sGZrVm+R5RDVDvlUm9hmisCJ/q7wLUQ51Xo7/5SyLdrl1lTwtGYtEenVdYBYY5pV1mDdo01AvpAyn64GITbbe7FgCe02O2eS2c0l8/Dao+yb7kXQ3BP0fkvBddXFPrPS6oMd1aNJUqaks5vphwQMgSh1toWG6fsENbRhdbFkbn0PARUD/70LIkMbZ+ys+GFxbGjLDxlj7oXQiJ8AY2eby6IiMS753kI/z3on7eL9Ae1Wc+hpH1nwtGQUplviql32eZC6dB8aCEItQykCUfSnlKn2ORCSApkGZRC3boSgLFBhNGolaZYWCtLqmD5hL1BO2dXQ1BDRAP1od2CcBmeg+s03JiHGu9hFzUX5MEHvvXWJt4TDUG4a8NZPmHT23CCNWs9bIdbK62T1hd+UuBnCMaTrzO9bbC+JEuo7M/AlOoGG1hKvP8HP0ciWf7ihqX1rVbUt/pcfQMLl6tzJcvWN5+ob/IdJvRtl4ayvOkL0jbH1jUlSnqTTlHmagNLOSJTdvU1BoU2DOZdhNoGXow1TS0TwgZxyebmF7rEifp7bH6B6af/aptfOCjPatX5hUZxJtvNJMR79gnIq2jLbSIfwcJ8yHZTJ/LRoJ160q5O2JbNSNij85u+B+GdfDLLgw/Iun0ZepUSSFUvpvKiLelU/bZ0V9LJ3kk/AikVmQmDv4LM/FSTpgNhYInIkT4EYTznTu8AuH2NCErR+WEFN9H421mefUiW4WFHl67ZCmoPMKGvvrxuIZSBIpyHWH3goyDoUftC5pA437aQ6ZHe/+TGhUyXOJNldVrwAlyH/ll84NJUWFb5PqZe72NmN6q/tX7ZohLTAhnep06xv4Dzvc6l4dUW9lkN2rHfVe9gEF7d8nVIhFcvP9bh/G/ZSrbE8A5/x65+hS2bwFqPXiePQ3jHKjn/65ukLY+tFbZMOqHy7JC9xEfQbXRnRuD3pxkWcQuDLYpGxKCHZJ9lWnQbLgpNYzl3ZiZB/m/uTKuHzWRYaFrd5840edT71mb0cXwt9IOf13D+24ZvIr1ibubj/McrllVdrqyqi5TVOITXH+S8k1m038LxQlX/2WYZoOgCZiG8eJjzbyjUr4Q17yOyV5HyyyA/DnK/QV71mC6X38HA3PICyK/qfU5NQ8LZMM0mUvakIzylsufkULNTtPuapCNln1LVUhsUbqd+wX4k5ThXikBYQ5Hl4xJVdwTkMyDvtVFcjoYpxsJJe3NKHYMZCsTTCPFArzw+j98TnQKdS02cb8C5SUvCmXTE5QyhNQVmbYT68Ihb62zQekJap0+LQnrEwOjRUabrCoRxrnn5dAm53S2+815eLr7HLQd5aQvMTx0yDYdtLaJaPQaJCHiG9PGJ7dGesUEFsAUAa8GL+iWbW6agweN3U5Kgj/zZQqd+2eyJQqfotrkXoOIG3ThUN3oG3LlRm9XRqR4JZkmmWcz9P2m3ztOHIN8Qs5Z/DvIIyB8yyvfm5WVQv0ZW0K8G+ckV5J0gn19BPgny/7KQl4KtZ0C+GdYy+8vkWH4K5iIlTVDO2ZQj6ZR95COiHmbY00lne8oRn+9Px+XskXVSi1dfYm4Y1hug5w151FvhogmGqlAm7FFdbCEzLv14VOGnSfezVgYZgv79pM2d9nt2pv25wD6DMS3Tql+wnXDenQ6SkP3MLScWoQwYbRRkB9NhknWIRO5Gfwfy/prgflC//W0RqYivW/zgTRaAuwP6OX4rehbWaTMjnB8taOv6FEL0naKNXQQ/9r2cD+jzx5qWFEvYh5Mqm0h3a646aF0qe1hE43enG1HHDuu3mnHOX9Db2HiLmBnp1btVVu4Tbqh3EQ9rEhjwiO8+q0Hn7COcP59LC0w8WEhPTMjTqp/Ue0Qf0w9+vROwbpQf5WnnpC1Tjp1T9m8lndvkEPgjWxossBhaGBSJPMd0G4Pg52AIUWChxRaPqDfnxBr0cet6dRHkpy3kIt3XxJoW5LO5tVRArKVE4iNuraxOrqZgPibC2gDr2aEDy4clvqXcCvIZkF9Q9Tpqa0iU7Ew6m9OdYpA/BVOOPaLhijFL1aCe+fW6mJuPHwT9ikPWaT0J8k6QHzenNcp6cmmFgUD4fQ/8zoPfJwrssYvml616qPpaVazTvbA+78F+uCVpTzgm3GL9qds7rtu5zS27rRbd+njVIbsguW7cCuv46sOc/43eL1a1JNWEffc0Ux9WMztl9YF51zTrzeC3wiPg/8OnYB3PqC+H6bFaYpNe98IK8El3psGzLyPSOAN+33ma839hVCehy+2cVqOZLrEwHIeGNWVPOSCxn1GHGfCwF+T5oj8jlpty78JlCKf/u5wfojinYVo3OWWHxQdrTTph9dEmho2ebjl4wODeWaf1gD8xgegSdTGqN2SIKJb2Lz4O4YfpDjQhGWsovSjH9ghMIiZTnNfq9fyibVsKJnpPyDXaHjGnljXhQUY1OuhR/yFXvZs96tdyEr+s6ydFeH9sbmMpaUpRnu+A/HOQv6XbsUe2W7TjFINVz5+K4mjxiLp6Ffymnue0Zo/CejJRAs1v71E2Kddhp8XgAvmBTs2f7hIryigtvkQXXHGjonx0gvOX9XIsVV9ksj6JMboeZLPOLP9z8TClQ6sOJEqY3zC/PeqEqh+UNtoxJ1Z21cZpWX5fihf3YASbtwlWrFm74Vt+htclyqpbdatu1a26VbfqVt2qW3Wr7n/biX++tSHKfW+4CZr4Ws38rLSX+9e4udr8Xx6093ke1we05/nKC7omrQuIN5b28FI4tNeXeGJpLy/tzf4sy8d0D3p4tPe79HX9mvZ8l76sX9MGjtdwAUJ7tmkPMu01v4r7/2lP+gz6p/fMtH6hPc0fLurhX8f0lGICf43Xl29nBXqzf2EryEcZJmCNKT1fzK2bdJfleniz521krzGjHa7h9V+9qd/5D7z+5f+xenbud9iy951ogPWIGxG3IAYQOxAHEfcjJhFPIJ5BPI+YRnwf8WPE64hOJBVYj7gRcQtiALEDcRBxP2IS8QTiGcTziGnE9xE/RryO6MQKvB5xI+IWxABiB+Ig4n7EJOIJxDOI5xHTiO8jfox4HdGJDWY94kbELYgBxA7EQcT9iEnEE4hnEM8jphHfR/wY8TqiExvIesSNiFsQA4gdiIOI+xGTiCcQzyCeR0wjvo/4MeJ1RKfr/3//bnRmOfFpE3+n2RF/NvFvmh3xZRN/ptkRP3a1hT7xYb9uoU/81x9YyInvesgifOK3Jv5HsyM+6y9b5J/4q2cswie+6lkLOfFTd1rET3zUT1jIiX/6JQs58U2/bSEnfmni/zM74pN+10JO/NE/sZATX/Q1i/wTP3SOD9rkiA/6fgs58T8T/5zZEd9zn4U+8TvXWOgTn/OARf6Iv7nVQk58zW9axE/8zB9YyImPuccifcS/PGMhJ77lWQs58SsT/5fZEZ8y8XeZHfEnP2+hT3zJr1jIiR85x4dscsSHPG4hJ/7jixZy4jsm/qgl7QfbNfEZky/iMbbq98gRfzHxFZNv4im26hfJET8x8RGTb+Ihtuo3yRH/MPENk2/iGa4uEj/xCxOfcM438rS+XiR+4g+OmuInnuAPiugTPzDxAZNv4gEeKpJ+4v8lvl/yTTy/Vv06OerXic83Z3/U/3IR+xN/L/H15uyP+jNF0k/8vMTHm7M/8fwW0Sf+XeLbzdkf9TuL5J/4dYlPN+cbeUqfKKJP/LnEl5uzP+q/VESf+HGrTPrEg/t2EX0at4jvNmd/1Lca18jRuEZ8tjn7o/67RfRz/5MwabI/6v+kiD7x0xIfbc7+qH+tiP2Jf1YxxU88s1bjKjnilyU+2Zxv5Om8v4g+8cf2mPSJJ9ZqXCZH/LCzpv6HeGD7isRP/K/E95qzP/GMFomfxvVxkz7xuA4UsR+N+8TXmrM/6rcW0Sd+VuJjzdkf9d8skn/iXyW+1Zz9Uf+DIvrEr0p8qjnfyFPZU6T8iD+1x6RPPKkzRfSJH7XUpE88qLNF9In/lPhOc/ZHfat5DTma1xw26ROPqdW8hxzxl1aZ9Imn9Pki8RM/KfGR5uyP+q8U0Sf+UeIbzdkf9a3mVeSIX9Rr0ice0fEi+sQfSnyhOfuj/sUi+sQPSnygOfsTD6hp3hasq3vQWxFs3rbJ+xtRELno2SEEE/SV2+7tvSf37PHfN+SfHZr9EBngr/C5pFK5b0j8lWPvbqVydCw+ULln9NFKudf0ruF+pVLuJK6MD0zCr/jTSkXKh3r3DSmV/Y+Pij9MlBif0CW0b9l40Q2yiYGRXuERz8ZHILyJMbl7tXJgqFvSIHUP9U/krwzJGZ8YGx+YiD8OCdE14rv37dPTpv/5pZ42Ohd+RDQQgUxc797hPkjQWFz+6HHr4chgxKZ3wZORz3llbzw+Mbz70XiO3eN/7jxKIefnq6wQzbyidtP1F7HuOE3PlwlvK6L/qEn/GivEKkeh/1ITlpv06Tk54cvPFdbjGlP8d5r06Xk44boi6Rff+13nfCz3FBWffxOuZYXPqc2PtR5EGzDT83FCenDvwnS6TM+la/FZOTM9byd8zfSBj7lXaMBn16RPz6sJSaHE9PybcDs+C6dreh5OSPrm9JMbxDJlpufxhPQ83lx+lP9x1K81Pf8npPcFxG9q1j+A6aL4xz+wFeDB9cvXP3LfMel/8gtbAUbYyvXnmEm/+pqtAJ8x/Zm6ufxeMLXfWRsrwCplZf3XMH4VE3aY/t9vHSt4b2SV/zcwTNKn90fHUP9yEf23FZ1nV1WW1y+1SD9hWlHwnyWx2aH+qXVs2fya9f+O8k/9H+q/WkSf3D9i36Ga3qecQ30yjDleytdVU/zEs33uBnyOUCT9vzDp0/uyq6g/rq6sf92k34PPL3puxnRohfpe83NGsj/JkT+ceEPN9jfr22x6/OZ6SvqVyvL9F6HbZvqGsR3XH6gfKtJ/G/NudMQv/t9TYMRffgIAHhqx3SgrAgA=' [s390x]=$'0 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zm+~g4qGMWkz!V-<8U34UK!rA;qjt%CX&zQYxpZ z5~-6SR>$RVDd(tihAJ_i6tg-shf6su@Qrp7P=;F`pE(dSZu5dFzySPKnv%-m%p~J6y^Or@U@T%qhjJ zp4-t?dDoOTO^Las7~E)G(+w}HseL)!7-_KA_@xY^Z|fQ%mt0fZb-1w}FLULuk1+a% z)?E`grWb!3VGN8a{FjKUu#Dd^5~;%@#XuC!b4MD3q9#R&s0u^)>yQfdxCHER@xP5U zMsRG7+qWOW^X)@3jXRl-Uq8s&)~?Pp7BC!Lug`*BkL>C_+%?J=)Y>Usf-u}D<32oc UUrDGfU#NBS^Ms<}j5d1yKNYYiAOHXW From afe0ce62ac8df42f1726c22fc8d3c572267c049a Mon Sep 17 00:00:00 2001 From: jkool702 Date: Thu, 21 May 2026 17:01:32 -0400 Subject: [PATCH 04/10] initial test - superscalar prefetch engine --- BENCHMARKS/benchmark.out | 5780 ++++++++++++++++++------------------- forkrun_ring.c | 39 +- forkrun_ring.native.so | Bin 141896 -> 0 bytes forkrun_ring.x86-64-v2.so | Bin 137800 -> 0 bytes forkrun_ring.x86-64-v3.so | Bin 145992 -> 0 bytes forkrun_ring.x86-64-v4.so | Bin 145992 -> 0 bytes 6 files changed, 2900 insertions(+), 2919 deletions(-) delete mode 100755 forkrun_ring.native.so delete mode 100755 forkrun_ring.x86-64-v2.so delete mode 100755 forkrun_ring.x86-64-v3.so delete mode 100755 forkrun_ring.x86-64-v4.so diff --git a/BENCHMARKS/benchmark.out b/BENCHMARKS/benchmark.out index d9f525ac..4f79822c 100644 --- a/BENCHMARKS/benchmark.out +++ b/BENCHMARKS/benchmark.out @@ -12,11 +12,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.134s -user 0m6.445s -sys 0m20.314s +real 0m1.143s +user 0m6.340s +sys 0m20.616s -CPU UTILIZATION: 23.597 / 28 +CPU UTILIZATION: 23.583 / 28 ----------------------------------------- @@ -34,11 +34,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.126s -user 0m6.316s -sys 0m20.486s +real 0m1.131s +user 0m6.372s +sys 0m20.580s -CPU UTILIZATION: 23.802 / 28 +CPU UTILIZATION: 23.830 / 28 ----------------------------------------- @@ -47,19 +47,19 @@ CPU UTILIZATION: 23.802 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 383 processed | 2 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.126s -user 0m6.409s -sys 0m20.582s +real 0m1.135s +user 0m6.503s +sys 0m20.667s -CPU UTILIZATION: 23.970 / 28 +CPU UTILIZATION: 23.938 / 28 ----------------------------------------- @@ -68,20 +68,20 @@ CPU UTILIZATION: 23.970 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 384 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 383 assigned | 382 processed | 1 I stole | 2 stolen from me Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 384 processed | 2 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= 0 -real 0m1.129s -user 0m6.427s -sys 0m20.523s +real 0m1.137s +user 0m6.473s +sys 0m20.769s -CPU UTILIZATION: 23.870 / 28 +CPU UTILIZATION: 23.959 / 28 ----------------------------------------- @@ -98,11 +98,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.196s -user 0m6.495s -sys 0m22.123s +real 0m1.204s +user 0m6.414s +sys 0m22.317s -CPU UTILIZATION: 23.928 / 28 +CPU UTILIZATION: 23.862 / 28 ----------------------------------------- @@ -112,19 +112,19 @@ CPU UTILIZATION: 23.928 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 11 assigned | 11 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.197s -user 0m6.556s -sys 0m22.209s +real 0m1.233s +user 0m6.482s +sys 0m22.237s -CPU UTILIZATION: 24.030 / 28 +CPU UTILIZATION: 23.291 / 28 ----------------------------------------- @@ -133,19 +133,19 @@ CPU UTILIZATION: 24.030 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.201s -user 0m6.473s -sys 0m22.346s +real 0m1.206s +user 0m6.587s +sys 0m22.398s -CPU UTILIZATION: 23.995 / 28 +CPU UTILIZATION: 24.033 / 28 ----------------------------------------- @@ -154,20 +154,20 @@ CPU UTILIZATION: 23.995 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 381 processed | 0 I stole | 1 stolen from me Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 25555 -real 0m1.203s -user 0m6.586s -sys 0m22.348s +real 0m1.206s +user 0m6.578s +sys 0m22.553s -CPU UTILIZATION: 24.051 / 28 +CPU UTILIZATION: 24.155 / 28 ----------------------------------------- @@ -176,19 +176,19 @@ CPU UTILIZATION: 24.051 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m1.898s -user 0m25.451s -sys 0m21.682s +user 0m25.420s +sys 0m21.972s -CPU UTILIZATION: 24.832 / 28 +CPU UTILIZATION: 24.969 / 28 ----------------------------------------- @@ -206,11 +206,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.893s -user 0m25.344s -sys 0m21.887s +real 0m1.899s +user 0m25.462s +sys 0m22.022s -CPU UTILIZATION: 24.950 / 28 +CPU UTILIZATION: 25.004 / 28 ----------------------------------------- @@ -219,19 +219,19 @@ CPU UTILIZATION: 24.950 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.896s -user 0m25.473s -sys 0m21.958s +real 0m1.897s +user 0m25.718s +sys 0m21.872s -CPU UTILIZATION: 25.016 / 28 +CPU UTILIZATION: 25.086 / 28 ----------------------------------------- @@ -241,19 +241,19 @@ CPU UTILIZATION: 25.016 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 100000000 -real 0m1.901s -user 0m25.394s -sys 0m22.168s +real 0m1.905s +user 0m25.550s +sys 0m22.217s -CPU UTILIZATION: 25.019 / 28 +CPU UTILIZATION: 25.074 / 28 ----------------------------------------- @@ -270,11 +270,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.656s -user 0m1.637s -sys 0m13.801s +real 0m0.659s +user 0m1.588s +sys 0m13.802s -CPU UTILIZATION: 23.533 / 28 +CPU UTILIZATION: 23.353 / 28 ----------------------------------------- @@ -283,20 +283,20 @@ CPU UTILIZATION: 23.533 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.665s -user 0m1.597s -sys 0m13.814s +real 0m0.660s +user 0m1.583s +sys 0m13.871s -CPU UTILIZATION: 23.174 / 28 +CPU UTILIZATION: 23.415 / 28 ----------------------------------------- @@ -305,19 +305,19 @@ CPU UTILIZATION: 23.174 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 2 I stole | 3 stolen from me -Node 1 (Phys 1): 383 assigned | 380 processed | 1 I stole | 4 stolen from me -Node 2 (Phys 2): 379 assigned | 383 processed | 5 I stole | 1 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 387 assigned | 385 processed | 0 I stole | 2 stolen from me +Node 1 (Phys 1): 383 assigned | 385 processed | 2 I stole | 0 stolen from me +Node 2 (Phys 2): 376 assigned | 379 processed | 4 I stole | 1 stolen from me +Node 3 (Phys 3): 381 assigned | 378 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.6%) +Total Cross-Socket Traffic: 6 chunks (0.4%) ================================================================= -real 0m0.707s -user 0m2.520s -sys 0m14.116s +real 0m0.706s +user 0m2.475s +sys 0m14.221s -CPU UTILIZATION: 23.530 / 28 +CPU UTILIZATION: 23.648 / 28 ----------------------------------------- @@ -326,20 +326,20 @@ CPU UTILIZATION: 23.530 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 381 processed | 0 I stole | 4 stolen from me -Node 1 (Phys 1): 380 assigned | 385 processed | 5 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 386 assigned | 385 processed | 2 I stole | 3 stolen from me +Node 1 (Phys 1): 380 assigned | 379 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 380 assigned | 382 processed | 2 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 4 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.3%) +Total Cross-Socket Traffic: 9 chunks (0.6%) ================================================================= 0 -real 0m0.708s -user 0m2.499s -sys 0m14.175s +real 0m0.707s +user 0m2.455s +sys 0m14.192s -CPU UTILIZATION: 23.550 / 28 +CPU UTILIZATION: 23.545 / 28 ----------------------------------------- @@ -356,11 +356,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.700s -user 0m2.375s -sys 0m14.124s +real 0m0.702s +user 0m2.378s +sys 0m14.153s -CPU UTILIZATION: 23.570 / 28 +CPU UTILIZATION: 23.548 / 28 ----------------------------------------- @@ -378,11 +378,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m0.697s -user 0m2.418s -sys 0m14.010s +real 0m0.709s +user 0m2.339s +sys 0m14.228s -CPU UTILIZATION: 23.569 / 28 +CPU UTILIZATION: 23.366 / 28 ----------------------------------------- @@ -391,19 +391,19 @@ CPU UTILIZATION: 23.569 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 3 I stole | 3 stolen from me -Node 1 (Phys 1): 380 assigned | 382 processed | 5 I stole | 3 stolen from me -Node 2 (Phys 2): 383 assigned | 385 processed | 4 I stole | 2 stolen from me -Node 3 (Phys 3): 381 assigned | 377 processed | 4 I stole | 8 stolen from me +Node 0 (Phys 0): 385 assigned | 383 processed | 1 I stole | 3 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 380 assigned | 383 processed | 3 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 16 chunks (1.0%) +Total Cross-Socket Traffic: 6 chunks (0.4%) ================================================================= -real 0m0.747s -user 0m3.202s -sys 0m14.578s +real 0m0.746s +user 0m3.307s +sys 0m14.524s -CPU UTILIZATION: 23.801 / 28 +CPU UTILIZATION: 23.902 / 28 ----------------------------------------- @@ -412,20 +412,20 @@ CPU UTILIZATION: 23.801 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 383 processed | 8 I stole | 7 stolen from me -Node 1 (Phys 1): 379 assigned | 383 processed | 8 I stole | 4 stolen from me -Node 2 (Phys 2): 384 assigned | 379 processed | 3 I stole | 8 stolen from me -Node 3 (Phys 3): 382 assigned | 382 processed | 3 I stole | 3 stolen from me +Node 0 (Phys 0): 388 assigned | 385 processed | 6 I stole | 9 stolen from me +Node 1 (Phys 1): 381 assigned | 383 processed | 9 I stole | 7 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 4 I stole | 4 stolen from me +Node 3 (Phys 3): 376 assigned | 377 processed | 5 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 22 chunks (1.4%) +Total Cross-Socket Traffic: 24 chunks (1.6%) ================================================================= 5965 -real 0m0.750s -user 0m3.318s -sys 0m14.538s +real 0m0.751s +user 0m3.225s +sys 0m14.683s -CPU UTILIZATION: 23.808 / 28 +CPU UTILIZATION: 23.845 / 28 ----------------------------------------- @@ -434,19 +434,19 @@ CPU UTILIZATION: 23.808 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.406s -user 0m21.600s -sys 0m14.301s +real 0m1.412s +user 0m21.450s +sys 0m14.437s -CPU UTILIZATION: 25.534 / 28 +CPU UTILIZATION: 25.415 / 28 ----------------------------------------- @@ -464,11 +464,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.410s -user 0m21.520s -sys 0m14.330s +real 0m1.413s +user 0m21.407s +sys 0m14.485s -CPU UTILIZATION: 25.425 / 28 +CPU UTILIZATION: 25.401 / 28 ----------------------------------------- @@ -477,19 +477,19 @@ CPU UTILIZATION: 25.425 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 378 assigned | 379 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m1.456s -user 0m22.422s -sys 0m14.717s +real 0m1.461s +user 0m22.252s +sys 0m14.849s -CPU UTILIZATION: 25.507 / 28 +CPU UTILIZATION: 25.394 / 28 ----------------------------------------- @@ -499,19 +499,19 @@ CPU UTILIZATION: 25.507 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.456s -user 0m22.282s -sys 0m14.904s +real 0m1.463s +user 0m22.290s +sys 0m14.905s -CPU UTILIZATION: 25.539 / 28 +CPU UTILIZATION: 25.423 / 28 ----------------------------------------- @@ -528,11 +528,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.129s -user 0m6.352s -sys 0m20.363s +real 0m1.135s +user 0m6.361s +sys 0m20.553s -CPU UTILIZATION: 23.662 / 28 +CPU UTILIZATION: 23.712 / 28 ----------------------------------------- @@ -550,11 +550,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.130s -user 0m6.335s -sys 0m20.393s +real 0m1.131s +user 0m6.378s +sys 0m20.548s -CPU UTILIZATION: 23.653 / 28 +CPU UTILIZATION: 23.807 / 28 ----------------------------------------- @@ -563,19 +563,19 @@ CPU UTILIZATION: 23.653 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.133s -user 0m6.463s -sys 0m20.488s +real 0m1.137s +user 0m6.387s +sys 0m20.759s -CPU UTILIZATION: 23.787 / 28 +CPU UTILIZATION: 23.875 / 28 ----------------------------------------- @@ -584,20 +584,20 @@ CPU UTILIZATION: 23.787 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 381 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 384 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 0 -real 0m1.132s -user 0m6.403s -sys 0m20.565s +real 0m1.131s +user 0m6.382s +sys 0m20.744s -CPU UTILIZATION: 23.823 / 28 +CPU UTILIZATION: 23.984 / 28 ----------------------------------------- @@ -606,19 +606,19 @@ CPU UTILIZATION: 23.823 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.194s -user 0m6.394s -sys 0m22.155s +real 0m1.204s +user 0m6.492s +sys 0m22.211s -CPU UTILIZATION: 23.910 / 28 +CPU UTILIZATION: 23.839 / 28 ----------------------------------------- @@ -636,11 +636,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.206s -user 0m6.520s -sys 0m22.087s +real 0m1.211s +user 0m6.582s +sys 0m22.260s -CPU UTILIZATION: 23.720 / 28 +CPU UTILIZATION: 23.816 / 28 ----------------------------------------- @@ -649,19 +649,19 @@ CPU UTILIZATION: 23.720 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.196s -user 0m6.571s -sys 0m22.146s +real 0m1.204s +user 0m6.666s +sys 0m22.307s -CPU UTILIZATION: 24.010 / 28 +CPU UTILIZATION: 24.063 / 28 ----------------------------------------- @@ -670,20 +670,20 @@ CPU UTILIZATION: 24.010 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 384 processed | 3 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 381 processed | 0 I stole | 2 stolen from me Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= 25555 -real 0m1.204s -user 0m6.641s -sys 0m22.266s +real 0m1.208s +user 0m6.785s +sys 0m22.267s -CPU UTILIZATION: 24.009 / 28 +CPU UTILIZATION: 24.049 / 28 ----------------------------------------- @@ -700,11 +700,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.887s -user 0m25.342s -sys 0m21.773s +real 0m1.893s +user 0m25.430s +sys 0m21.868s -CPU UTILIZATION: 24.968 / 28 +CPU UTILIZATION: 24.985 / 28 ----------------------------------------- @@ -722,11 +722,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.899s -user 0m25.284s -sys 0m21.939s +real 0m1.897s +user 0m25.365s +sys 0m21.937s -CPU UTILIZATION: 24.867 / 28 +CPU UTILIZATION: 24.935 / 28 ----------------------------------------- @@ -735,19 +735,19 @@ CPU UTILIZATION: 24.867 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m1.894s -user 0m25.543s -sys 0m21.868s +real 0m1.899s +user 0m25.370s +sys 0m22.222s -CPU UTILIZATION: 25.032 / 28 +CPU UTILIZATION: 25.061 / 28 ----------------------------------------- @@ -756,20 +756,20 @@ CPU UTILIZATION: 25.032 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 382 assigned | 381 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m1.898s -user 0m25.491s -sys 0m22.015s +real 0m1.905s +user 0m25.434s +sys 0m22.319s -CPU UTILIZATION: 25.029 / 28 +CPU UTILIZATION: 25.067 / 28 ----------------------------------------- @@ -778,19 +778,19 @@ CPU UTILIZATION: 25.029 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.677s -user 0m1.544s -sys 0m13.796s +real 0m0.665s +user 0m1.619s +sys 0m13.835s -CPU UTILIZATION: 22.658 / 28 +CPU UTILIZATION: 23.239 / 28 ----------------------------------------- @@ -808,11 +808,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.663s -user 0m1.602s -sys 0m13.811s +real 0m0.661s +user 0m1.582s +sys 0m13.798s -CPU UTILIZATION: 23.247 / 28 +CPU UTILIZATION: 23.267 / 28 ----------------------------------------- @@ -821,19 +821,19 @@ CPU UTILIZATION: 23.247 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 384 processed | 1 I stole | 3 stolen from me -Node 1 (Phys 1): 380 assigned | 382 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 379 assigned | 381 processed | 4 I stole | 2 stolen from me -Node 3 (Phys 3): 382 assigned | 380 processed | 1 I stole | 3 stolen from me +Node 0 (Phys 0): 389 assigned | 385 processed | 2 I stole | 6 stolen from me +Node 1 (Phys 1): 380 assigned | 383 processed | 6 I stole | 3 stolen from me +Node 2 (Phys 2): 378 assigned | 380 processed | 4 I stole | 2 stolen from me +Node 3 (Phys 3): 380 assigned | 379 processed | 3 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.6%) +Total Cross-Socket Traffic: 15 chunks (1.0%) ================================================================= real 0m0.709s -user 0m2.495s -sys 0m14.150s +user 0m2.460s +sys 0m14.254s -CPU UTILIZATION: 23.476 / 28 +CPU UTILIZATION: 23.574 / 28 ----------------------------------------- @@ -842,20 +842,20 @@ CPU UTILIZATION: 23.476 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 4 I stole | 4 stolen from me -Node 1 (Phys 1): 378 assigned | 380 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 385 assigned | 382 processed | 0 I stole | 3 stolen from me -Node 3 (Phys 3): 381 assigned | 382 processed | 3 I stole | 2 stolen from me +Node 0 (Phys 0): 391 assigned | 390 processed | 7 I stole | 8 stolen from me +Node 1 (Phys 1): 384 assigned | 382 processed | 5 I stole | 7 stolen from me +Node 2 (Phys 2): 377 assigned | 376 processed | 8 I stole | 9 stolen from me +Node 3 (Phys 3): 375 assigned | 379 processed | 11 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 10 chunks (0.7%) +Total Cross-Socket Traffic: 31 chunks (2.0%) ================================================================= 0 -real 0m0.705s -user 0m2.522s -sys 0m14.121s +real 0m0.714s +user 0m2.513s +sys 0m14.201s -CPU UTILIZATION: 23.607 / 28 +CPU UTILIZATION: 23.408 / 28 ----------------------------------------- @@ -872,11 +872,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.702s -user 0m2.373s -sys 0m14.093s +real 0m0.701s +user 0m2.368s +sys 0m14.145s -CPU UTILIZATION: 23.455 / 28 +CPU UTILIZATION: 23.556 / 28 ----------------------------------------- @@ -895,10 +895,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) 4539 real 0m0.706s -user 0m2.376s -sys 0m14.163s +user 0m2.417s +sys 0m14.177s -CPU UTILIZATION: 23.426 / 28 +CPU UTILIZATION: 23.504 / 28 ----------------------------------------- @@ -907,19 +907,19 @@ CPU UTILIZATION: 23.426 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 387 processed | 5 I stole | 2 stolen from me -Node 1 (Phys 1): 376 assigned | 377 processed | 5 I stole | 4 stolen from me -Node 2 (Phys 2): 383 assigned | 382 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 384 assigned | 381 processed | 1 I stole | 4 stolen from me +Node 0 (Phys 0): 381 assigned | 385 processed | 8 I stole | 4 stolen from me +Node 1 (Phys 1): 374 assigned | 378 processed | 8 I stole | 4 stolen from me +Node 2 (Phys 2): 388 assigned | 383 processed | 0 I stole | 5 stolen from me +Node 3 (Phys 3): 384 assigned | 381 processed | 3 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 14 chunks (0.9%) +Total Cross-Socket Traffic: 19 chunks (1.2%) ================================================================= -real 0m0.753s -user 0m3.282s -sys 0m14.486s +real 0m0.748s +user 0m3.268s +sys 0m14.583s -CPU UTILIZATION: 23.596 / 28 +CPU UTILIZATION: 23.864 / 28 ----------------------------------------- @@ -928,20 +928,20 @@ CPU UTILIZATION: 23.596 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 383 processed | 2 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 380 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 386 assigned | 384 processed | 1 I stole | 3 stolen from me +Node 1 (Phys 1): 386 assigned | 384 processed | 0 I stole | 2 stolen from me +Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 372 assigned | 375 processed | 3 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.3%) +Total Cross-Socket Traffic: 5 chunks (0.3%) ================================================================= 5965 -real 0m0.751s -user 0m3.291s -sys 0m14.497s +real 0m0.754s +user 0m3.248s +sys 0m14.644s -CPU UTILIZATION: 23.685 / 28 +CPU UTILIZATION: 23.729 / 28 ----------------------------------------- @@ -951,18 +951,18 @@ CPU UTILIZATION: 23.685 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 11 assigned | 11 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.435s -user 0m21.302s -sys 0m14.177s +real 0m1.403s +user 0m21.385s +sys 0m14.404s -CPU UTILIZATION: 24.724 / 28 +CPU UTILIZATION: 25.508 / 28 ----------------------------------------- @@ -980,11 +980,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.410s -user 0m21.467s -sys 0m14.376s +real 0m1.415s +user 0m21.391s +sys 0m14.535s -CPU UTILIZATION: 25.420 / 28 +CPU UTILIZATION: 25.389 / 28 ----------------------------------------- @@ -993,19 +993,19 @@ CPU UTILIZATION: 25.420 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.456s -user 0m22.315s -sys 0m14.753s +real 0m1.460s +user 0m22.277s +sys 0m14.838s -CPU UTILIZATION: 25.458 / 28 +CPU UTILIZATION: 25.421 / 28 ----------------------------------------- @@ -1014,20 +1014,20 @@ CPU UTILIZATION: 25.458 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m1.457s -user 0m22.357s -sys 0m14.804s +real 0m1.456s +user 0m22.289s +sys 0m14.878s -CPU UTILIZATION: 25.505 / 28 +CPU UTILIZATION: 25.526 / 28 ----------------------------------------- @@ -1044,11 +1044,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.105s -user 0m6.067s -sys 0m19.929s +real 0m1.103s +user 0m6.078s +sys 0m20.089s -CPU UTILIZATION: 23.525 / 28 +CPU UTILIZATION: 23.723 / 28 ----------------------------------------- @@ -1057,20 +1057,20 @@ CPU UTILIZATION: 23.525 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.101s -user 0m6.090s -sys 0m19.948s +real 0m1.130s +user 0m6.049s +sys 0m20.008s -CPU UTILIZATION: 23.649 / 28 +CPU UTILIZATION: 23.059 / 28 ----------------------------------------- @@ -1079,19 +1079,19 @@ CPU UTILIZATION: 23.649 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m1.103s -user 0m6.098s -sys 0m20.149s +real 0m1.107s +user 0m6.046s +sys 0m20.402s -CPU UTILIZATION: 23.796 / 28 +CPU UTILIZATION: 23.891 / 28 ----------------------------------------- @@ -1100,20 +1100,20 @@ CPU UTILIZATION: 23.796 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 1 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 0 -real 0m1.103s -user 0m6.053s -sys 0m20.175s +real 0m1.108s +user 0m6.209s +sys 0m20.239s -CPU UTILIZATION: 23.778 / 28 +CPU UTILIZATION: 23.870 / 28 ----------------------------------------- @@ -1131,10 +1131,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m1.161s -user 0m6.052s -sys 0m21.574s +user 0m6.248s +sys 0m21.560s -CPU UTILIZATION: 23.795 / 28 +CPU UTILIZATION: 23.951 / 28 ----------------------------------------- @@ -1143,20 +1143,20 @@ CPU UTILIZATION: 23.795 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.167s -user 0m6.249s -sys 0m21.490s +real 0m1.177s +user 0m6.138s +sys 0m21.824s -CPU UTILIZATION: 23.769 / 28 +CPU UTILIZATION: 23.757 / 28 ----------------------------------------- @@ -1165,19 +1165,19 @@ CPU UTILIZATION: 23.769 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 384 processed | 3 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.1%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= real 0m1.164s -user 0m6.302s -sys 0m21.533s +user 0m6.248s +sys 0m21.761s -CPU UTILIZATION: 23.913 / 28 +CPU UTILIZATION: 24.062 / 28 ----------------------------------------- @@ -1186,20 +1186,20 @@ CPU UTILIZATION: 23.913 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 25555 -real 0m1.167s -user 0m6.260s -sys 0m21.745s +real 0m1.175s +user 0m6.298s +sys 0m21.901s -CPU UTILIZATION: 23.997 / 28 +CPU UTILIZATION: 23.999 / 28 ----------------------------------------- @@ -1216,11 +1216,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.850s -user 0m24.900s -sys 0m21.340s +real 0m1.858s +user 0m25.032s +sys 0m21.346s -CPU UTILIZATION: 24.994 / 28 +CPU UTILIZATION: 24.961 / 28 ----------------------------------------- @@ -1238,11 +1238,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.863s -user 0m24.839s -sys 0m21.467s +real 0m1.867s +user 0m24.848s +sys 0m21.679s -CPU UTILIZATION: 24.855 / 28 +CPU UTILIZATION: 24.920 / 28 ----------------------------------------- @@ -1251,19 +1251,19 @@ CPU UTILIZATION: 24.855 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me ------------------------------------------------------------------ -Total Cross-Socket Traffic: 0 chunks (0.0%) +Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +----------------------------------------------------------------- +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.853s -user 0m25.018s -sys 0m21.483s +real 0m1.859s +user 0m25.014s +sys 0m21.506s -CPU UTILIZATION: 25.094 / 28 +CPU UTILIZATION: 25.024 / 28 ----------------------------------------- @@ -1272,20 +1272,20 @@ CPU UTILIZATION: 25.094 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me Node 3 (Phys 3): 382 assigned | 382 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m1.866s -user 0m24.969s -sys 0m21.720s +real 0m1.868s +user 0m24.926s +sys 0m21.840s -CPU UTILIZATION: 25.020 / 28 +CPU UTILIZATION: 25.035 / 28 ----------------------------------------- @@ -1302,11 +1302,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.661s -user 0m1.470s -sys 0m13.769s +real 0m0.657s +user 0m1.509s +sys 0m13.777s -CPU UTILIZATION: 23.054 / 28 +CPU UTILIZATION: 23.266 / 28 ----------------------------------------- @@ -1324,11 +1324,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.662s -user 0m1.574s -sys 0m13.718s +real 0m0.659s +user 0m1.532s +sys 0m13.803s -CPU UTILIZATION: 23.099 / 28 +CPU UTILIZATION: 23.270 / 28 ----------------------------------------- @@ -1337,19 +1337,19 @@ CPU UTILIZATION: 23.099 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 385 processed | 3 I stole | 2 stolen from me -Node 1 (Phys 1): 383 assigned | 385 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 379 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 379 assigned | 378 processed | 2 I stole | 3 stolen from me +Node 0 (Phys 0): 392 assigned | 386 processed | 1 I stole | 7 stolen from me +Node 1 (Phys 1): 382 assigned | 385 processed | 5 I stole | 2 stolen from me +Node 2 (Phys 2): 378 assigned | 376 processed | 2 I stole | 4 stolen from me +Node 3 (Phys 3): 375 assigned | 380 processed | 5 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.6%) +Total Cross-Socket Traffic: 13 chunks (0.9%) ================================================================= -real 0m0.700s -user 0m2.381s -sys 0m14.027s +real 0m0.704s +user 0m2.396s +sys 0m14.124s -CPU UTILIZATION: 23.440 / 28 +CPU UTILIZATION: 23.465 / 28 ----------------------------------------- @@ -1358,20 +1358,20 @@ CPU UTILIZATION: 23.440 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 387 assigned | 384 processed | 2 I stole | 5 stolen from me -Node 1 (Phys 1): 381 assigned | 384 processed | 6 I stole | 3 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 3 I stole | 4 stolen from me -Node 3 (Phys 3): 378 assigned | 379 processed | 5 I stole | 4 stolen from me +Node 0 (Phys 0): 384 assigned | 387 processed | 6 I stole | 3 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 5 I stole | 5 stolen from me +Node 2 (Phys 2): 383 assigned | 380 processed | 2 I stole | 5 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 5 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 16 chunks (1.0%) +Total Cross-Socket Traffic: 18 chunks (1.2%) ================================================================= 0 -real 0m0.703s -user 0m2.452s -sys 0m14.066s +real 0m0.702s +user 0m2.391s +sys 0m14.070s -CPU UTILIZATION: 23.496 / 28 +CPU UTILIZATION: 23.448 / 28 ----------------------------------------- @@ -1388,11 +1388,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.691s -user 0m2.342s -sys 0m13.921s +real 0m0.694s +user 0m2.287s +sys 0m13.985s -CPU UTILIZATION: 23.535 / 28 +CPU UTILIZATION: 23.446 / 28 ----------------------------------------- @@ -1410,11 +1410,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m0.718s -user 0m2.275s -sys 0m13.848s +real 0m0.715s +user 0m2.224s +sys 0m13.917s -CPU UTILIZATION: 22.455 / 28 +CPU UTILIZATION: 22.574 / 28 ----------------------------------------- @@ -1423,19 +1423,19 @@ CPU UTILIZATION: 22.455 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 2 I stole | 2 stolen from me -Node 1 (Phys 1): 383 assigned | 381 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 381 processed | 2 I stole | 0 stolen from me +Node 0 (Phys 0): 387 assigned | 384 processed | 6 I stole | 9 stolen from me +Node 1 (Phys 1): 382 assigned | 380 processed | 9 I stole | 11 stolen from me +Node 2 (Phys 2): 382 assigned | 383 processed | 11 I stole | 10 stolen from me +Node 3 (Phys 3): 376 assigned | 380 processed | 8 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.3%) +Total Cross-Socket Traffic: 34 chunks (2.2%) ================================================================= -real 0m0.737s -user 0m3.167s -sys 0m14.312s +real 0m0.740s +user 0m3.140s +sys 0m14.400s -CPU UTILIZATION: 23.716 / 28 +CPU UTILIZATION: 23.702 / 28 ----------------------------------------- @@ -1444,20 +1444,20 @@ CPU UTILIZATION: 23.716 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 382 assigned | 380 processed | 0 I stole | 2 stolen from me -Node 1 (Phys 1): 383 assigned | 382 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 382 assigned | 386 processed | 4 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 383 assigned | 380 processed | 0 I stole | 3 stolen from me +Node 1 (Phys 1): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 383 processed | 2 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 381 processed | 1 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= 5965 -real 0m0.755s -user 0m3.070s -sys 0m14.351s +real 0m0.762s +user 0m3.187s +sys 0m14.209s -CPU UTILIZATION: 23.074 / 28 +CPU UTILIZATION: 22.829 / 28 ----------------------------------------- @@ -1467,18 +1467,18 @@ CPU UTILIZATION: 23.074 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 11 assigned | 11 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.423s -user 0m21.123s -sys 0m14.012s +real 0m1.402s +user 0m21.278s +sys 0m14.270s -CPU UTILIZATION: 24.690 / 28 +CPU UTILIZATION: 25.355 / 28 ----------------------------------------- @@ -1496,11 +1496,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.411s -user 0m20.954s -sys 0m14.165s +real 0m1.452s +user 0m20.529s +sys 0m14.153s -CPU UTILIZATION: 24.889 / 28 +CPU UTILIZATION: 23.885 / 28 ----------------------------------------- @@ -1510,18 +1510,18 @@ CPU UTILIZATION: 24.889 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 381 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.445s -user 0m22.222s -sys 0m14.580s +real 0m1.450s +user 0m22.197s +sys 0m14.591s -CPU UTILIZATION: 25.468 / 28 +CPU UTILIZATION: 25.371 / 28 ----------------------------------------- @@ -1531,19 +1531,19 @@ CPU UTILIZATION: 25.468 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 385 assigned | 384 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 380 assigned | 379 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 378 assigned | 380 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 100000000 -real 0m1.465s -user 0m21.807s -sys 0m14.746s +real 0m1.459s +user 0m21.589s +sys 0m14.630s -CPU UTILIZATION: 24.950 / 28 +CPU UTILIZATION: 24.824 / 28 ----------------------------------------- @@ -1560,11 +1560,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.365s -user 0m34.841s -sys 0m0.713s +real 0m1.362s +user 0m34.637s +sys 0m0.722s -CPU UTILIZATION: 26.046 / 28 +CPU UTILIZATION: 25.961 / 28 ----------------------------------------- @@ -1573,20 +1573,20 @@ CPU UTILIZATION: 26.046 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.361s -user 0m34.814s -sys 0m0.676s +real 0m1.360s +user 0m34.622s +sys 0m0.726s -CPU UTILIZATION: 26.076 / 28 +CPU UTILIZATION: 25.991 / 28 ----------------------------------------- @@ -1595,19 +1595,19 @@ CPU UTILIZATION: 26.076 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 370 assigned | 370 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 386 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 389 assigned | 388 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 376 assigned | 376 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 377 assigned | 377 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m1.356s -user 0m34.674s -sys 0m0.864s +real 0m1.362s +user 0m34.743s +sys 0m0.832s -CPU UTILIZATION: 26.207 / 28 +CPU UTILIZATION: 26.119 / 28 ----------------------------------------- @@ -1616,20 +1616,20 @@ CPU UTILIZATION: 26.207 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 364 assigned | 364 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 391 assigned | 391 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 388 assigned | 388 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 392 assigned | 392 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 370 assigned | 370 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.365s -user 0m34.826s -sys 0m0.859s +real 0m1.370s +user 0m34.954s +sys 0m0.958s -CPU UTILIZATION: 26.142 / 28 +CPU UTILIZATION: 26.213 / 28 ----------------------------------------- @@ -1646,11 +1646,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.363s -user 0m34.704s -sys 0m0.765s +real 0m1.369s +user 0m34.772s +sys 0m0.775s -CPU UTILIZATION: 26.022 / 28 +CPU UTILIZATION: 25.965 / 28 ----------------------------------------- @@ -1659,20 +1659,20 @@ CPU UTILIZATION: 26.022 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.366s -user 0m34.841s -sys 0m0.887s +real 0m1.401s +user 0m34.344s +sys 0m0.852s -CPU UTILIZATION: 26.155 / 28 +CPU UTILIZATION: 25.122 / 28 ----------------------------------------- @@ -1681,19 +1681,19 @@ CPU UTILIZATION: 26.155 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 388 assigned | 388 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 371 assigned | 370 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 383 assigned | 384 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 386 assigned | 385 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 392 assigned | 392 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 363 assigned | 364 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m1.364s -user 0m34.919s -sys 0m0.873s +real 0m1.368s +user 0m34.963s +sys 0m0.858s -CPU UTILIZATION: 26.240 / 28 +CPU UTILIZATION: 26.184 / 28 ----------------------------------------- @@ -1702,20 +1702,20 @@ CPU UTILIZATION: 26.240 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 388 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 390 assigned | 388 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 365 assigned | 365 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 389 assigned | 389 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 371 assigned | 371 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 391 assigned | 391 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 376 assigned | 376 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.366s -user 0m34.880s -sys 0m0.996s +real 0m1.373s +user 0m34.868s +sys 0m1.024s -CPU UTILIZATION: 26.263 / 28 +CPU UTILIZATION: 26.141 / 28 ----------------------------------------- @@ -1732,11 +1732,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.368s -user 0m34.874s -sys 0m0.756s +real 0m1.365s +user 0m34.869s +sys 0m0.775s -CPU UTILIZATION: 26.045 / 28 +CPU UTILIZATION: 26.112 / 28 ----------------------------------------- @@ -1754,11 +1754,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.365s -user 0m34.854s +real 0m1.366s +user 0m34.841s sys 0m0.802s -CPU UTILIZATION: 26.121 / 28 +CPU UTILIZATION: 26.092 / 28 ----------------------------------------- @@ -1767,19 +1767,19 @@ CPU UTILIZATION: 26.121 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 389 assigned | 389 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 387 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 375 assigned | 374 processed | 0 I stole | 1 stolen from me Node 2 (Phys 2): 386 assigned | 386 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 370 assigned | 370 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.370s -user 0m34.974s -sys 0m0.928s +real 0m1.373s +user 0m34.984s +sys 0m0.896s -CPU UTILIZATION: 26.205 / 28 +CPU UTILIZATION: 26.132 / 28 ----------------------------------------- @@ -1788,20 +1788,20 @@ CPU UTILIZATION: 26.205 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 378 assigned | 378 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 389 assigned | 389 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 375 assigned | 375 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 377 assigned | 377 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25555 -real 0m1.372s -user 0m35.051s -sys 0m0.920s +real 0m1.377s +user 0m35.092s +sys 0m0.980s -CPU UTILIZATION: 26.217 / 28 +CPU UTILIZATION: 26.196 / 28 ----------------------------------------- @@ -1818,11 +1818,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.614s -user 0m41.647s -sys 0m0.498s +real 0m1.615s +user 0m41.545s +sys 0m0.557s -CPU UTILIZATION: 26.112 / 28 +CPU UTILIZATION: 26.069 / 28 ----------------------------------------- @@ -1840,11 +1840,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.613s -user 0m41.655s -sys 0m0.460s +real 0m1.620s +user 0m41.625s +sys 0m0.519s -CPU UTILIZATION: 26.109 / 28 +CPU UTILIZATION: 26.014 / 28 ----------------------------------------- @@ -1853,19 +1853,19 @@ CPU UTILIZATION: 26.109 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 392 assigned | 392 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 371 assigned | 371 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 390 assigned | 390 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 374 assigned | 374 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 390 assigned | 389 processed | 3 I stole | 4 stolen from me +Node 1 (Phys 1): 370 assigned | 369 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 380 assigned | 380 processed | 1 I stole | 1 stolen from me +Node 3 (Phys 3): 387 assigned | 389 processed | 3 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 8 chunks (0.5%) ================================================================= -real 0m1.709s -user 0m44.315s -sys 0m0.766s +real 0m1.704s +user 0m44.001s +sys 0m0.706s -CPU UTILIZATION: 26.378 / 28 +CPU UTILIZATION: 26.236 / 28 ----------------------------------------- @@ -1874,20 +1874,20 @@ CPU UTILIZATION: 26.378 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 392 assigned | 393 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 378 assigned | 377 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 363 assigned | 362 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 394 assigned | 395 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 378 assigned | 378 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 371 assigned | 371 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 392 assigned | 392 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 386 assigned | 386 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.701s -user 0m44.044s -sys 0m0.731s +real 0m1.715s +user 0m44.250s +sys 0m0.744s -CPU UTILIZATION: 26.322 / 28 +CPU UTILIZATION: 26.235 / 28 ----------------------------------------- @@ -1904,11 +1904,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.617s -user 0m41.813s -sys 0m0.484s +real 0m1.616s +user 0m41.593s +sys 0m0.540s -CPU UTILIZATION: 26.157 / 28 +CPU UTILIZATION: 26.072 / 28 ----------------------------------------- @@ -1918,19 +1918,19 @@ CPU UTILIZATION: 26.157 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 11 assigned | 11 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m1.636s -user 0m40.982s -sys 0m0.529s +real 0m1.621s +user 0m41.564s +sys 0m0.536s -CPU UTILIZATION: 25.373 / 28 +CPU UTILIZATION: 25.971 / 28 ----------------------------------------- @@ -1939,19 +1939,19 @@ CPU UTILIZATION: 25.373 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 391 assigned | 392 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 378 assigned | 377 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 379 assigned | 380 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 378 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 379 assigned | 380 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 387 assigned | 386 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 378 assigned | 377 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m1.712s -user 0m44.157s -sys 0m0.783s +real 0m1.707s +user 0m44.058s +sys 0m0.812s -CPU UTILIZATION: 26.250 / 28 +CPU UTILIZATION: 26.285 / 28 ----------------------------------------- @@ -1960,20 +1960,20 @@ CPU UTILIZATION: 26.250 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 378 assigned | 378 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 398 assigned | 398 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 388 assigned | 388 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 363 assigned | 363 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 390 assigned | 390 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 374 assigned | 374 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 394 assigned | 395 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 369 assigned | 368 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 5965 -real 0m1.706s -user 0m44.053s -sys 0m0.801s +real 0m1.712s +user 0m44.171s +sys 0m0.812s -CPU UTILIZATION: 26.291 / 28 +CPU UTILIZATION: 26.275 / 28 ----------------------------------------- @@ -1990,11 +1990,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.620s -user 0m41.592s -sys 0m0.509s +real 0m1.625s +user 0m41.839s +sys 0m0.505s -CPU UTILIZATION: 25.988 / 28 +CPU UTILIZATION: 26.057 / 28 ----------------------------------------- @@ -2005,18 +2005,18 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 13 assigned | 13 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4539 -real 0m1.614s -user 0m41.763s -sys 0m0.544s +real 0m1.652s +user 0m41.180s +sys 0m0.517s -CPU UTILIZATION: 26.212 / 28 +CPU UTILIZATION: 25.240 / 28 ----------------------------------------- @@ -2025,19 +2025,19 @@ CPU UTILIZATION: 26.212 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 372 assigned | 374 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 394 assigned | 393 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 389 assigned | 388 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 372 assigned | 372 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 386 assigned | 386 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 367 assigned | 367 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 393 assigned | 393 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.709s -user 0m44.213s -sys 0m0.764s +real 0m1.722s +user 0m44.375s +sys 0m0.782s -CPU UTILIZATION: 26.317 / 28 +CPU UTILIZATION: 26.223 / 28 ----------------------------------------- @@ -2046,20 +2046,20 @@ CPU UTILIZATION: 26.317 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 387 assigned | 387 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 391 assigned | 391 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 373 assigned | 375 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 395 assigned | 395 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 391 assigned | 389 processed | 0 I stole | 2 stolen from me Node 3 (Phys 3): 368 assigned | 368 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= 5965 -real 0m1.705s -user 0m44.102s -sys 0m0.753s +real 0m1.717s +user 0m44.367s +sys 0m0.809s -CPU UTILIZATION: 26.307 / 28 +CPU UTILIZATION: 26.311 / 28 ----------------------------------------- @@ -2068,19 +2068,19 @@ CPU UTILIZATION: 26.307 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 13 assigned | 13 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.169s -user 0m1.769s -sys 0m0.781s +real 0m0.167s +user 0m1.744s +sys 0m0.754s -CPU UTILIZATION: 15.088 / 28 +CPU UTILIZATION: 14.958 / 28 ----------------------------------------- @@ -2098,11 +2098,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.170s -user 0m1.762s -sys 0m0.744s +real 0m0.166s +user 0m1.804s +sys 0m0.720s -CPU UTILIZATION: 14.741 / 28 +CPU UTILIZATION: 15.204 / 28 ----------------------------------------- @@ -2111,19 +2111,19 @@ CPU UTILIZATION: 14.741 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 404 processed | 40 I stole | 21 stolen from me -Node 1 (Phys 1): 412 assigned | 407 processed | 26 I stole | 31 stolen from me -Node 2 (Phys 2): 366 assigned | 358 processed | 21 I stole | 29 stolen from me -Node 3 (Phys 3): 364 assigned | 358 processed | 18 I stole | 24 stolen from me +Node 0 (Phys 0): 384 assigned | 387 processed | 33 I stole | 30 stolen from me +Node 1 (Phys 1): 370 assigned | 362 processed | 20 I stole | 28 stolen from me +Node 2 (Phys 2): 429 assigned | 444 processed | 38 I stole | 23 stolen from me +Node 3 (Phys 3): 344 assigned | 334 processed | 22 I stole | 32 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 105 chunks (6.9%) +Total Cross-Socket Traffic: 113 chunks (7.4%) ================================================================= -real 0m0.183s -user 0m1.868s -sys 0m0.898s +real 0m0.186s +user 0m1.801s +sys 0m0.948s -CPU UTILIZATION: 15.114 / 28 +CPU UTILIZATION: 14.779 / 28 ----------------------------------------- @@ -2132,20 +2132,20 @@ CPU UTILIZATION: 15.114 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 430 assigned | 442 processed | 43 I stole | 31 stolen from me -Node 1 (Phys 1): 364 assigned | 383 processed | 46 I stole | 27 stolen from me -Node 2 (Phys 2): 350 assigned | 316 processed | 9 I stole | 43 stolen from me -Node 3 (Phys 3): 383 assigned | 386 processed | 37 I stole | 34 stolen from me +Node 0 (Phys 0): 367 assigned | 360 processed | 22 I stole | 29 stolen from me +Node 1 (Phys 1): 398 assigned | 406 processed | 25 I stole | 17 stolen from me +Node 2 (Phys 2): 382 assigned | 393 processed | 26 I stole | 15 stolen from me +Node 3 (Phys 3): 380 assigned | 368 processed | 15 I stole | 27 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 135 chunks (8.8%) +Total Cross-Socket Traffic: 88 chunks (5.8%) ================================================================= 0 -real 0m0.183s -user 0m1.883s -sys 0m0.849s +real 0m0.187s +user 0m1.856s +sys 0m0.947s -CPU UTILIZATION: 14.928 / 28 +CPU UTILIZATION: 14.989 / 28 ----------------------------------------- @@ -2162,11 +2162,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.744s -user 0m9.160s -sys 0m7.441s +real 0m0.746s +user 0m9.124s +sys 0m7.646s -CPU UTILIZATION: 22.313 / 28 +CPU UTILIZATION: 22.479 / 28 ----------------------------------------- @@ -2184,11 +2184,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.747s -user 0m9.194s -sys 0m7.550s +real 0m0.756s +user 0m9.141s +sys 0m7.743s -CPU UTILIZATION: 22.414 / 28 +CPU UTILIZATION: 22.333 / 28 ----------------------------------------- @@ -2197,19 +2197,19 @@ CPU UTILIZATION: 22.414 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 379 assigned | 379 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 380 assigned | 381 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= -real 0m0.751s -user 0m9.264s -sys 0m7.528s +real 0m0.757s +user 0m9.309s +sys 0m7.683s -CPU UTILIZATION: 22.359 / 28 +CPU UTILIZATION: 22.446 / 28 ----------------------------------------- @@ -2218,20 +2218,20 @@ CPU UTILIZATION: 22.359 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 380 assigned | 380 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 383 assigned | 384 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 378 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 383 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 379 assigned | 378 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 381 assigned | 382 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m0.748s -user 0m9.217s -sys 0m7.691s +real 0m0.762s +user 0m9.230s +sys 0m7.894s -CPU UTILIZATION: 22.604 / 28 +CPU UTILIZATION: 22.472 / 28 ----------------------------------------- @@ -2248,11 +2248,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.730s -user 0m9.064s -sys 0m7.233s +real 0m0.739s +user 0m9.091s +sys 0m7.383s -CPU UTILIZATION: 22.324 / 28 +CPU UTILIZATION: 22.292 / 28 ----------------------------------------- @@ -2271,10 +2271,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) 100000000 real 0m0.744s -user 0m9.133s -sys 0m7.308s +user 0m9.149s +sys 0m7.506s -CPU UTILIZATION: 22.098 / 28 +CPU UTILIZATION: 22.385 / 28 ----------------------------------------- @@ -2283,19 +2283,19 @@ CPU UTILIZATION: 22.098 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 379 assigned | 378 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 380 assigned | 380 processed | 1 I stole | 1 stolen from me +Node 3 (Phys 3): 379 assigned | 380 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= -real 0m0.731s -user 0m9.166s -sys 0m7.323s +real 0m0.750s +user 0m9.222s +sys 0m7.513s -CPU UTILIZATION: 22.556 / 28 +CPU UTILIZATION: 22.313 / 28 ----------------------------------------- @@ -2304,20 +2304,20 @@ CPU UTILIZATION: 22.556 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 382 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 385 assigned | 386 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 380 assigned | 379 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 379 assigned | 378 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 1 chunks (0.1%) ================================================================= 100000000 -real 0m0.742s -user 0m9.215s -sys 0m7.348s +real 0m0.746s +user 0m9.143s +sys 0m7.654s -CPU UTILIZATION: 22.322 / 28 +CPU UTILIZATION: 22.516 / 28 ----------------------------------------- @@ -2326,19 +2326,19 @@ CPU UTILIZATION: 22.322 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 12 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 12 assigned | 13 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (2.0%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.113s -user 0m0.047s -sys 0m0.143s +real 0m0.112s +user 0m0.052s +sys 0m0.136s -CPU UTILIZATION: 1.681 / 28 +CPU UTILIZATION: 1.678 / 28 ----------------------------------------- @@ -2347,20 +2347,20 @@ CPU UTILIZATION: 1.681 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 13 assigned | 12 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 13 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 12 assigned | 11 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (2.0%) ================================================================= 0 -real 0m0.117s -user 0m0.049s -sys 0m0.146s +real 0m0.115s +user 0m0.052s +sys 0m0.142s -CPU UTILIZATION: 1.666 / 28 +CPU UTILIZATION: 1.686 / 28 ----------------------------------------- @@ -2369,19 +2369,19 @@ CPU UTILIZATION: 1.666 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 390 assigned | 396 processed | 6 I stole | 0 stolen from me -Node 1 (Phys 1): 385 assigned | 384 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 379 assigned | 377 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 373 assigned | 370 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 385 assigned | 391 processed | 6 I stole | 0 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 381 assigned | 378 processed | 0 I stole | 3 stolen from me +Node 3 (Phys 3): 377 assigned | 374 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 8 chunks (0.5%) +Total Cross-Socket Traffic: 6 chunks (0.4%) ================================================================= -real 0m0.125s -user 0m0.229s -sys 0m0.242s +real 0m0.132s +user 0m0.243s +sys 0m0.258s -CPU UTILIZATION: 3.768 / 28 +CPU UTILIZATION: 3.795 / 28 ----------------------------------------- @@ -2390,20 +2390,20 @@ CPU UTILIZATION: 3.768 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 389 assigned | 405 processed | 16 I stole | 0 stolen from me -Node 1 (Phys 1): 382 assigned | 377 processed | 3 I stole | 8 stolen from me -Node 2 (Phys 2): 379 assigned | 372 processed | 0 I stole | 7 stolen from me -Node 3 (Phys 3): 377 assigned | 373 processed | 0 I stole | 4 stolen from me +Node 0 (Phys 0): 382 assigned | 375 processed | 0 I stole | 7 stolen from me +Node 1 (Phys 1): 381 assigned | 378 processed | 3 I stole | 6 stolen from me +Node 2 (Phys 2): 387 assigned | 402 processed | 17 I stole | 2 stolen from me +Node 3 (Phys 3): 377 assigned | 372 processed | 2 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 19 chunks (1.2%) +Total Cross-Socket Traffic: 22 chunks (1.4%) ================================================================= 0 -real 0m0.123s -user 0m0.231s -sys 0m0.253s +real 0m0.129s +user 0m0.232s +sys 0m0.248s -CPU UTILIZATION: 3.934 / 28 +CPU UTILIZATION: 3.720 / 28 ----------------------------------------- @@ -2420,11 +2420,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.113s -user 0m0.089s -sys 0m0.216s +real 0m0.114s +user 0m0.098s +sys 0m0.224s -CPU UTILIZATION: 2.699 / 28 +CPU UTILIZATION: 2.824 / 28 ----------------------------------------- @@ -2442,11 +2442,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.112s -user 0m0.096s -sys 0m0.249s +real 0m0.120s +user 0m0.098s +sys 0m0.267s -CPU UTILIZATION: 3.080 / 28 +CPU UTILIZATION: 3.041 / 28 ----------------------------------------- @@ -2455,19 +2455,19 @@ CPU UTILIZATION: 3.080 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 387 assigned | 385 processed | 3 I stole | 5 stolen from me -Node 1 (Phys 1): 377 assigned | 381 processed | 5 I stole | 1 stolen from me -Node 2 (Phys 2): 378 assigned | 377 processed | 2 I stole | 3 stolen from me -Node 3 (Phys 3): 385 assigned | 384 processed | 2 I stole | 3 stolen from me +Node 0 (Phys 0): 387 assigned | 385 processed | 1 I stole | 3 stolen from me +Node 1 (Phys 1): 382 assigned | 383 processed | 5 I stole | 4 stolen from me +Node 2 (Phys 2): 383 assigned | 381 processed | 1 I stole | 3 stolen from me +Node 3 (Phys 3): 375 assigned | 378 processed | 5 I stole | 2 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 12 chunks (0.8%) ================================================================= -real 0m0.150s -user 0m0.578s -sys 0m0.558s +real 0m0.154s +user 0m0.570s +sys 0m0.584s -CPU UTILIZATION: 7.573 / 28 +CPU UTILIZATION: 7.493 / 28 ----------------------------------------- @@ -2476,20 +2476,20 @@ CPU UTILIZATION: 7.573 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 383 assigned | 383 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 379 assigned | 379 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 381 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 385 assigned | 386 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 376 assigned | 377 processed | 2 I stole | 1 stolen from me +Node 2 (Phys 2): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 385 assigned | 384 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= 100000000 -real 0m0.146s -user 0m0.570s -sys 0m0.617s +real 0m0.160s +user 0m0.588s +sys 0m0.625s -CPU UTILIZATION: 8.130 / 28 +CPU UTILIZATION: 7.581 / 28 ----------------------------------------- @@ -2506,11 +2506,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.106s -user 0m0.114s -sys 0m0.215s +real 0m0.114s +user 0m0.092s +sys 0m0.234s -CPU UTILIZATION: 3.103 / 28 +CPU UTILIZATION: 2.859 / 28 ----------------------------------------- @@ -2528,11 +2528,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.113s -user 0m0.104s -sys 0m0.250s +real 0m0.123s +user 0m0.121s +sys 0m0.256s -CPU UTILIZATION: 3.132 / 28 +CPU UTILIZATION: 3.065 / 28 ----------------------------------------- @@ -2541,19 +2541,19 @@ CPU UTILIZATION: 3.132 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 386 assigned | 387 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 381 assigned | 383 processed | 3 I stole | 1 stolen from me -Node 2 (Phys 2): 378 assigned | 376 processed | 1 I stole | 3 stolen from me -Node 3 (Phys 3): 382 assigned | 381 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 382 assigned | 384 processed | 5 I stole | 3 stolen from me +Node 1 (Phys 1): 382 assigned | 384 processed | 3 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 381 processed | 3 I stole | 4 stolen from me +Node 3 (Phys 3): 381 assigned | 378 processed | 1 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 7 chunks (0.5%) +Total Cross-Socket Traffic: 12 chunks (0.8%) ================================================================= -real 0m0.144s -user 0m0.569s -sys 0m0.529s +real 0m0.150s +user 0m0.580s +sys 0m0.563s -CPU UTILIZATION: 7.625 / 28 +CPU UTILIZATION: 7.620 / 28 ----------------------------------------- @@ -2562,20 +2562,20 @@ CPU UTILIZATION: 7.625 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 391 assigned | 389 processed | 2 I stole | 4 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 378 assigned | 379 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 376 assigned | 377 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 380 assigned | 381 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 384 assigned | 384 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 2 I stole | 2 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 7 chunks (0.5%) +Total Cross-Socket Traffic: 6 chunks (0.4%) ================================================================= 100000000 -real 0m0.147s -user 0m0.545s -sys 0m0.616s +real 0m0.148s +user 0m0.582s +sys 0m0.579s -CPU UTILIZATION: 7.897 / 28 +CPU UTILIZATION: 7.844 / 28 ----------------------------------------- @@ -2585,18 +2585,18 @@ CPU UTILIZATION: 7.897 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 13 assigned | 13 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 13 assigned | 13 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 12 assigned | 12 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 11 assigned | 11 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.169s -user 0m1.652s -sys 0m0.728s +real 0m0.171s +user 0m1.612s +sys 0m0.732s -CPU UTILIZATION: 14.082 / 28 +CPU UTILIZATION: 13.707 / 28 ----------------------------------------- @@ -2614,11 +2614,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.171s -user 0m1.588s -sys 0m0.701s +real 0m0.173s +user 0m1.679s +sys 0m0.728s -CPU UTILIZATION: 13.385 / 28 +CPU UTILIZATION: 13.913 / 28 ----------------------------------------- @@ -2627,19 +2627,19 @@ CPU UTILIZATION: 13.385 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 351 assigned | 344 processed | 16 I stole | 23 stolen from me -Node 1 (Phys 1): 400 assigned | 402 processed | 14 I stole | 12 stolen from me -Node 2 (Phys 2): 398 assigned | 397 processed | 17 I stole | 18 stolen from me -Node 3 (Phys 3): 378 assigned | 384 processed | 18 I stole | 12 stolen from me +Node 0 (Phys 0): 387 assigned | 398 processed | 19 I stole | 8 stolen from me +Node 1 (Phys 1): 394 assigned | 393 processed | 11 I stole | 12 stolen from me +Node 2 (Phys 2): 380 assigned | 373 processed | 5 I stole | 12 stolen from me +Node 3 (Phys 3): 366 assigned | 363 processed | 6 I stole | 9 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 65 chunks (4.3%) +Total Cross-Socket Traffic: 41 chunks (2.7%) ================================================================= -real 0m0.182s -user 0m1.755s -sys 0m0.844s +real 0m0.176s +user 0m1.712s +sys 0m0.770s -CPU UTILIZATION: 14.280 / 28 +CPU UTILIZATION: 14.102 / 28 ----------------------------------------- @@ -2648,20 +2648,20 @@ CPU UTILIZATION: 14.280 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 391 assigned | 384 processed | 24 I stole | 31 stolen from me -Node 1 (Phys 1): 369 assigned | 363 processed | 19 I stole | 25 stolen from me -Node 2 (Phys 2): 403 assigned | 426 processed | 34 I stole | 11 stolen from me -Node 3 (Phys 3): 364 assigned | 354 processed | 21 I stole | 31 stolen from me +Node 0 (Phys 0): 412 assigned | 412 processed | 25 I stole | 25 stolen from me +Node 1 (Phys 1): 399 assigned | 383 processed | 16 I stole | 32 stolen from me +Node 2 (Phys 2): 362 assigned | 370 processed | 21 I stole | 13 stolen from me +Node 3 (Phys 3): 354 assigned | 362 processed | 23 I stole | 15 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 98 chunks (6.4%) +Total Cross-Socket Traffic: 85 chunks (5.6%) ================================================================= 0 -real 0m0.183s -user 0m1.716s -sys 0m0.831s +real 0m0.181s +user 0m1.686s +sys 0m0.811s -CPU UTILIZATION: 13.918 / 28 +CPU UTILIZATION: 13.795 / 28 ----------------------------------------- @@ -2678,11 +2678,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.713s -user 0m8.700s -sys 0m7.041s +real 0m0.724s +user 0m8.780s +sys 0m7.117s -CPU UTILIZATION: 22.077 / 28 +CPU UTILIZATION: 21.957 / 28 ----------------------------------------- @@ -2700,11 +2700,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.718s -user 0m8.794s -sys 0m7.133s +real 0m0.732s +user 0m8.796s +sys 0m7.258s -CPU UTILIZATION: 22.182 / 28 +CPU UTILIZATION: 21.931 / 28 ----------------------------------------- @@ -2713,19 +2713,19 @@ CPU UTILIZATION: 22.182 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 381 assigned | 381 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 384 assigned | 384 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 382 assigned | 382 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 380 assigned | 380 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 381 assigned | 383 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 382 processed | 1 I stole | 1 stolen from me +Node 3 (Phys 3): 383 assigned | 382 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= -real 0m0.713s -user 0m8.700s -sys 0m7.238s +real 0m0.726s +user 0m8.695s +sys 0m7.454s -CPU UTILIZATION: 22.353 / 28 +CPU UTILIZATION: 22.243 / 28 ----------------------------------------- @@ -2734,20 +2734,20 @@ CPU UTILIZATION: 22.353 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 385 assigned | 385 processed | 2 I stole | 2 stolen from me -Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 381 assigned | 381 processed | 1 I stole | 1 stolen from me -Node 3 (Phys 3): 379 assigned | 379 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 383 assigned | 382 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 382 assigned | 380 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 380 assigned | 382 processed | 2 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.3%) +Total Cross-Socket Traffic: 4 chunks (0.3%) ================================================================= 100000000 -real 0m0.718s -user 0m8.840s -sys 0m7.225s +real 0m0.728s +user 0m8.798s +sys 0m7.454s -CPU UTILIZATION: 22.374 / 28 +CPU UTILIZATION: 22.324 / 28 ----------------------------------------- @@ -2764,11 +2764,11 @@ Node 3 (Phys 3): 12 assigned | 12 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.705s -user 0m8.677s -sys 0m6.838s +real 0m0.715s +user 0m8.725s +sys 0m6.:00s -CPU UTILIZATION: 22.007 / 28 +CPU UTILIZATION: 13.041 / 28 ----------------------------------------- @@ -2786,11 +2786,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.714s -user 0m8.705s -sys 0m6.932s +real 0m0.721s +user 0m8.732s +sys 0m7.061s -CPU UTILIZATION: 21.900 / 28 +CPU UTILIZATION: 21.904 / 28 ----------------------------------------- @@ -2799,19 +2799,19 @@ CPU UTILIZATION: 21.900 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 387 assigned | 386 processed | 1 I stole | 2 stolen from me -Node 1 (Phys 1): 385 assigned | 384 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 375 assigned | 376 processed | 2 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 382 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 382 assigned | 381 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 382 assigned | 384 processed | 2 I stole | 0 stolen from me +Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.3%) +Total Cross-Socket Traffic: 3 chunks (0.2%) ================================================================= -real 0m0.704s -user 0m8.683s -sys 0m6.978s +real 0m0.713s +user 0m8.705s +sys 0m7.151s -CPU UTILIZATION: 22.245 / 28 +CPU UTILIZATION: 22.238 / 28 ----------------------------------------- @@ -2820,20 +2820,20 @@ CPU UTILIZATION: 22.245 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 384 assigned | 384 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 382 assigned | 383 processed | 1 I stole | 0 stolen from me Node 1 (Phys 1): 382 assigned | 382 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 380 assigned | 381 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 381 assigned | 380 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 384 assigned | 383 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 379 assigned | 379 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.2%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= 100000000 -real 0m0.712s -user 0m8.859s -sys 0m6.941s +real 0m0.717s +user 0m8.741s +sys 0m7.275s -CPU UTILIZATION: 22.191 / 28 +CPU UTILIZATION: 22.337 / 28 ----------------------------------------- @@ -2842,19 +2842,19 @@ CPU UTILIZATION: 22.191 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.199s -user 0m6.054s -sys 0m22.775s +real 0m1.204s +user 0m6.041s +sys 0m23.034s -CPU UTILIZATION: 24.044 / 28 +CPU UTILIZATION: 24.148 / 28 ----------------------------------------- @@ -2864,19 +2864,19 @@ CPU UTILIZATION: 24.044 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.195s -user 0m6.065s -sys 0m22.704s +real 0m1.206s +user 0m6.103s +sys 0m22.927s -CPU UTILIZATION: 24.074 / 28 +CPU UTILIZATION: 24.071 / 28 ----------------------------------------- @@ -2885,19 +2885,19 @@ CPU UTILIZATION: 24.074 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3489 assigned | 3493 processed | 175 I stole | 171 stolen from me -Node 1 (Phys 1): 3469 assigned | 3460 processed | 163 I stole | 172 stolen from me -Node 2 (Phys 2): 3194 assigned | 3169 processed | 160 I stole | 185 stolen from me -Node 3 (Phys 3): 3413 assigned | 3443 processed | 171 I stole | 141 stolen from me +Node 0 (Phys 0): 3420 assigned | 3451 processed | 173 I stole | 142 stolen from me +Node 1 (Phys 1): 3325 assigned | 3284 processed | 128 I stole | 169 stolen from me +Node 2 (Phys 2): 3388 assigned | 3392 processed | 161 I stole | 157 stolen from me +Node 3 (Phys 3): 3432 assigned | 3438 processed | 150 I stole | 144 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 669 chunks (4.9%) +Total Cross-Socket Traffic: 612 chunks (4.5%) ================================================================= -real 0m1.535s -user 0m9.188s -sys 0m23.504s +real 0m1.355s +user 0m9.210s +sys 0m23.677s -CPU UTILIZATION: 21.297 / 28 +CPU UTILIZATION: 24.270 / 28 ----------------------------------------- @@ -2906,20 +2906,20 @@ CPU UTILIZATION: 21.297 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3442 assigned | 3455 processed | 176 I stole | 163 stolen from me -Node 1 (Phys 1): 3389 assigned | 3385 processed | 184 I stole | 188 stolen from me -Node 2 (Phys 2): 3319 assigned | 3291 processed | 169 I stole | 197 stolen from me -Node 3 (Phys 3): 3415 assigned | 3434 processed | 178 I stole | 159 stolen from me +Node 0 (Phys 0): 3385 assigned | 3381 processed | 157 I stole | 161 stolen from me +Node 1 (Phys 1): 3382 assigned | 3374 processed | 158 I stole | 166 stolen from me +Node 2 (Phys 2): 3397 assigned | 3400 processed | 150 I stole | 147 stolen from me +Node 3 (Phys 3): 3401 assigned | 3410 processed | 141 I stole | 132 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 707 chunks (5.2%) +Total Cross-Socket Traffic: 606 chunks (4.5%) ================================================================= 0 -real 0m1.355s -user 0m9.134s -sys 0m23.451s +real 0m1.353s +user 0m9.157s +sys 0m23.733s -CPU UTILIZATION: 24.047 / 28 +CPU UTILIZATION: 24.308 / 28 ----------------------------------------- @@ -2930,17 +2930,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.323s -user 0m7.165s -sys 0m24.951s +real 0m1.328s +user 0m7.465s +sys 0m24.798s -CPU UTILIZATION: 24.275 / 28 +CPU UTILIZATION: 24.294 / 28 ----------------------------------------- @@ -2949,20 +2949,20 @@ CPU UTILIZATION: 24.275 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m1.334s -user 0m7.375s -sys 0m25.110s +real 0m1.335s +user 0m7.506s +sys 0m25.191s -CPU UTILIZATION: 24.351 / 28 +CPU UTILIZATION: 24.492 / 28 ----------------------------------------- @@ -2971,19 +2971,19 @@ CPU UTILIZATION: 24.351 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3406 assigned | 3386 processed | 182 I stole | 202 stolen from me -Node 1 (Phys 1): 3405 assigned | 3412 processed | 180 I stole | 173 stolen from me -Node 2 (Phys 2): 3383 assigned | 3376 processed | 169 I stole | 176 stolen from me -Node 3 (Phys 3): 3371 assigned | 3391 processed | 183 I stole | 163 stolen from me +Node 0 (Phys 0): 3353 assigned | 3314 processed | 196 I stole | 235 stolen from me +Node 1 (Phys 1): 3352 assigned | 3365 processed | 208 I stole | 195 stolen from me +Node 2 (Phys 2): 3431 assigned | 3418 processed | 181 I stole | 194 stolen from me +Node 3 (Phys 3): 3429 assigned | 3468 processed | 215 I stole | 176 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 714 chunks (5.3%) +Total Cross-Socket Traffic: 800 chunks (5.9%) ================================================================= -real 0m1.454s -user 0m10.015s -sys 0m25.747s +real 0m1.473s +user 0m10.111s +sys 0m26.130s -CPU UTILIZATION: 24.595 / 28 +CPU UTILIZATION: 24.603 / 28 ----------------------------------------- @@ -2992,20 +2992,20 @@ CPU UTILIZATION: 24.595 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3405 assigned | 3382 processed | 198 I stole | 221 stolen from me -Node 1 (Phys 1): 3391 assigned | 3393 processed | 196 I stole | 194 stolen from me -Node 2 (Phys 2): 3406 assigned | 3409 processed | 202 I stole | 199 stolen from me -Node 3 (Phys 3): 3363 assigned | 3381 processed | 191 I stole | 173 stolen from me +Node 0 (Phys 0): 3247 assigned | 3229 processed | 196 I stole | 214 stolen from me +Node 1 (Phys 1): 3378 assigned | 3405 processed | 212 I stole | 185 stolen from me +Node 2 (Phys 2): 3478 assigned | 3449 processed | 164 I stole | 193 stolen from me +Node 3 (Phys 3): 3462 assigned | 3482 processed | 190 I stole | 170 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 787 chunks (5.8%) +Total Cross-Socket Traffic: 762 chunks (5.6%) ================================================================= -28349 -real 0m1.467s -user 0m9.845s -sys 0m26.382s +28350 +real 0m1.537s +user 0m10.111s +sys 0m26.881s -CPU UTILIZATION: 24.694 / 28 +CPU UTILIZATION: 24.067 / 28 ----------------------------------------- @@ -3015,18 +3015,18 @@ CPU UTILIZATION: 24.694 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m2.077s -user 0m27.677s -sys 0m24.677s +real 0m2.083s +user 0m27.585s +sys 0m24.954s -CPU UTILIZATION: 25.206 / 28 +CPU UTILIZATION: 25.222 / 28 ----------------------------------------- @@ -3035,8 +3035,8 @@ CPU UTILIZATION: 25.206 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -3044,11 +3044,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m2.096s -user 0m27.628s -sys 0m25.176s +real 0m2.093s +user 0m27.719s +sys 0m25.316s -CPU UTILIZATION: 25.192 / 28 +CPU UTILIZATION: 25.339 / 28 ----------------------------------------- @@ -3057,19 +3057,19 @@ CPU UTILIZATION: 25.192 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3417 assigned | 3403 processed | 150 I stole | 164 stolen from me -Node 1 (Phys 1): 3389 assigned | 3383 processed | 144 I stole | 150 stolen from me -Node 2 (Phys 2): 3392 assigned | 3395 processed | 149 I stole | 146 stolen from me -Node 3 (Phys 3): 3367 assigned | 3384 processed | 152 I stole | 135 stolen from me +Node 0 (Phys 0): 3414 assigned | 3395 processed | 188 I stole | 207 stolen from me +Node 1 (Phys 1): 3419 assigned | 3406 processed | 190 I stole | 203 stolen from me +Node 2 (Phys 2): 3396 assigned | 3399 processed | 211 I stole | 208 stolen from me +Node 3 (Phys 3): 3336 assigned | 3365 processed | 189 I stole | 160 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 595 chunks (4.4%) +Total Cross-Socket Traffic: 778 chunks (5.7%) ================================================================= -real 0m2.191s -user 0m29.752s -sys 0m25.951s +real 0m2.201s +user 0m29.862s +sys 0m26.211s -CPU UTILIZATION: 25.423 / 28 +CPU UTILIZATION: 25.476 / 28 ----------------------------------------- @@ -3078,20 +3078,20 @@ CPU UTILIZATION: 25.423 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3406 assigned | 3385 processed | 164 I stole | 185 stolen from me -Node 1 (Phys 1): 3395 assigned | 3398 processed | 186 I stole | 183 stolen from me -Node 2 (Phys 2): 3406 assigned | 3397 processed | 156 I stole | 165 stolen from me -Node 3 (Phys 3): 3358 assigned | 3385 processed | 173 I stole | 146 stolen from me +Node 0 (Phys 0): 3390 assigned | 3400 processed | 200 I stole | 190 stolen from me +Node 1 (Phys 1): 3418 assigned | 3401 processed | 192 I stole | 209 stolen from me +Node 2 (Phys 2): 3386 assigned | 3373 processed | 181 I stole | 194 stolen from me +Node 3 (Phys 3): 3371 assigned | 3391 processed | 196 I stole | 176 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 679 chunks (5.0%) +Total Cross-Socket Traffic: 769 chunks (5.7%) ================================================================= 100000000 -real 0m2.207s -user 0m29.897s -sys 0m26.244s +real 0m2.214s +user 0m29.844s +sys 0m26.741s -CPU UTILIZATION: 25.437 / 28 +CPU UTILIZATION: 25.557 / 28 ----------------------------------------- @@ -3100,19 +3100,19 @@ CPU UTILIZATION: 25.437 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 104 assigned | 104 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.735s -user 0m1.851s -sys 0m15.645s +real 0m0.741s +user 0m1.948s +sys 0m15.674s -CPU UTILIZATION: 23.804 / 28 +CPU UTILIZATION: 23.781 / 28 ----------------------------------------- @@ -3122,19 +3122,19 @@ CPU UTILIZATION: 23.804 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.738s -user 0m1.960s -sys 0m15.577s +real 0m0.739s +user 0m1.935s +sys 0m15.710s -CPU UTILIZATION: 23.762 / 28 +CPU UTILIZATION: 23.876 / 28 ----------------------------------------- @@ -3143,19 +3143,19 @@ CPU UTILIZATION: 23.762 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3445 assigned | 3449 processed | 212 I stole | 208 stolen from me -Node 1 (Phys 1): 3409 assigned | 3375 processed | 175 I stole | 209 stolen from me -Node 2 (Phys 2): 3431 assigned | 3436 processed | 203 I stole | 198 stolen from me -Node 3 (Phys 3): 3280 assigned | 3305 processed | 192 I stole | 167 stolen from me +Node 0 (Phys 0): 3482 assigned | 3447 processed | 222 I stole | 257 stolen from me +Node 1 (Phys 1): 3338 assigned | 3327 processed | 234 I stole | 245 stolen from me +Node 2 (Phys 2): 3324 assigned | 3307 processed | 240 I stole | 257 stolen from me +Node 3 (Phys 3): 3421 assigned | 3484 processed | 274 I stole | 211 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 782 chunks (5.8%) +Total Cross-Socket Traffic: 970 chunks (7.2%) ================================================================= -real 0m1.076s -user 0m4.813s -sys 0m20.165s +real 0m1.088s +user 0m4.836s +sys 0m20.383s -CPU UTILIZATION: 23.213 / 28 +CPU UTILIZATION: 23.179 / 28 ----------------------------------------- @@ -3164,20 +3164,20 @@ CPU UTILIZATION: 23.213 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3479 assigned | 3444 processed | 219 I stole | 254 stolen from me -Node 1 (Phys 1): 3279 assigned | 3204 processed | 186 I stole | 261 stolen from me -Node 2 (Phys 2): 3374 assigned | 3421 processed | 241 I stole | 194 stolen from me -Node 3 (Phys 3): 3433 assigned | 3496 processed | 227 I stole | 164 stolen from me +Node 0 (Phys 0): 3391 assigned | 3381 processed | 257 I stole | 267 stolen from me +Node 1 (Phys 1): 3381 assigned | 3414 processed | 250 I stole | 217 stolen from me +Node 2 (Phys 2): 3404 assigned | 3377 processed | 192 I stole | 219 stolen from me +Node 3 (Phys 3): 3389 assigned | 3393 processed | 206 I stole | 202 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 873 chunks (6.4%) +Total Cross-Socket Traffic: 905 chunks (6.7%) ================================================================= 0 -real 0m1.204s -user 0m4.750s -sys 0m20.408s +real 0m1.080s +user 0m4.764s +sys 0m20.402s -CPU UTILIZATION: 20.895 / 28 +CPU UTILIZATION: 23.301 / 28 ----------------------------------------- @@ -3187,18 +3187,18 @@ CPU UTILIZATION: 20.895 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.832s -user 0m3.403s -sys 0m16.524s +real 0m0.828s +user 0m3.531s +sys 0m16.539s -CPU UTILIZATION: 23.950 / 28 +CPU UTILIZATION: 24.239 / 28 ----------------------------------------- @@ -3216,11 +3216,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m0.834s -user 0m3.410s -sys 0m16.837s +real 0m0.837s +user 0m3.487s +sys 0m16.930s -CPU UTILIZATION: 24.276 / 28 +CPU UTILIZATION: 24.393 / 28 ----------------------------------------- @@ -3229,19 +3229,19 @@ CPU UTILIZATION: 24.276 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3348 assigned | 3275 processed | 228 I stole | 301 stolen from me -Node 1 (Phys 1): 3478 assigned | 3454 processed | 252 I stole | 276 stolen from me -Node 2 (Phys 2): 3360 assigned | 3406 processed | 267 I stole | 221 stolen from me -Node 3 (Phys 3): 3379 assigned | 3430 processed | 272 I stole | 221 stolen from me +Node 0 (Phys 0): 3362 assigned | 3363 processed | 222 I stole | 221 stolen from me +Node 1 (Phys 1): 3402 assigned | 3432 processed | 235 I stole | 205 stolen from me +Node 2 (Phys 2): 3416 assigned | 3372 processed | 178 I stole | 222 stolen from me +Node 3 (Phys 3): 3385 assigned | 3398 processed | 220 I stole | 207 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1019 chunks (7.5%) +Total Cross-Socket Traffic: 855 chunks (6.3%) ================================================================= -real 0m1.214s -user 0m6.227s -sys 0m21.945s +real 0m1.190s +user 0m6.196s +sys 0m21.820s -CPU UTILIZATION: 23.205 / 28 +CPU UTILIZATION: 23.542 / 28 ----------------------------------------- @@ -3250,20 +3250,20 @@ CPU UTILIZATION: 23.205 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3374 assigned | 3369 processed | 246 I stole | 251 stolen from me -Node 1 (Phys 1): 3391 assigned | 3364 processed | 243 I stole | 270 stolen from me -Node 2 (Phys 2): 3425 assigned | 3390 processed | 209 I stole | 244 stolen from me -Node 3 (Phys 3): 3375 assigned | 3442 processed | 270 I stole | 203 stolen from me +Node 0 (Phys 0): 3422 assigned | 3432 processed | 248 I stole | 238 stolen from me +Node 1 (Phys 1): 3404 assigned | 3385 processed | 217 I stole | 236 stolen from me +Node 2 (Phys 2): 3308 assigned | 3318 processed | 236 I stole | 226 stolen from me +Node 3 (Phys 3): 3431 assigned | 3430 processed | 195 I stole | 196 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 968 chunks (7.1%) +Total Cross-Socket Traffic: 896 chunks (6.6%) ================================================================= -14835 -real 0m1.196s -user 0m6.247s -sys 0m22.064s +14837 +real 0m1.223s +user 0m6.308s +sys 0m22.387s -CPU UTILIZATION: 23.671 / 28 +CPU UTILIZATION: 23.462 / 28 ----------------------------------------- @@ -3273,18 +3273,18 @@ CPU UTILIZATION: 23.671 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.597s -user 0m24.226s -sys 0m16.756s +real 0m1.606s +user 0m24.114s +sys 0m16.960s -CPU UTILIZATION: 25.661 / 28 +CPU UTILIZATION: 25.575 / 28 ----------------------------------------- @@ -3294,19 +3294,19 @@ CPU UTILIZATION: 25.661 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.610s -user 0m24.265s +real 0m1.614s +user 0m24.240s sys 0m17.133s -CPU UTILIZATION: 25.713 / 28 +CPU UTILIZATION: 25.633 / 28 ----------------------------------------- @@ -3315,19 +3315,19 @@ CPU UTILIZATION: 25.713 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3383 assigned | 3393 processed | 320 I stole | 310 stolen from me -Node 1 (Phys 1): 3384 assigned | 3374 processed | 322 I stole | 332 stolen from me -Node 2 (Phys 2): 3388 assigned | 3407 processed | 318 I stole | 299 stolen from me -Node 3 (Phys 3): 3410 assigned | 3391 processed | 277 I stole | 296 stolen from me +Node 0 (Phys 0): 3396 assigned | 3369 processed | 277 I stole | 304 stolen from me +Node 1 (Phys 1): 3360 assigned | 3366 processed | 299 I stole | 293 stolen from me +Node 2 (Phys 2): 3418 assigned | 3410 processed | 282 I stole | 290 stolen from me +Node 3 (Phys 3): 3391 assigned | 3420 processed | 276 I stole | 247 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1237 chunks (9.1%) +Total Cross-Socket Traffic: 1134 chunks (8.4%) ================================================================= -real 0m1.891s -user 0m27.197s -sys 0m20.964s +real 0m1.899s +user 0m27.216s +sys 0m21.161s -CPU UTILIZATION: 25.468 / 28 +CPU UTILIZATION: 25.474 / 28 ----------------------------------------- @@ -3336,20 +3336,20 @@ CPU UTILIZATION: 25.468 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3436 assigned | 3399 processed | 309 I stole | 346 stolen from me -Node 1 (Phys 1): 3392 assigned | 3392 processed | 294 I stole | 294 stolen from me -Node 2 (Phys 2): 3388 assigned | 3399 processed | 289 I stole | 278 stolen from me -Node 3 (Phys 3): 3349 assigned | 3375 processed | 284 I stole | 258 stolen from me +Node 0 (Phys 0): 3422 assigned | 3405 processed | 354 I stole | 371 stolen from me +Node 1 (Phys 1): 3395 assigned | 3388 processed | 350 I stole | 357 stolen from me +Node 2 (Phys 2): 3393 assigned | 3393 processed | 339 I stole | 339 stolen from me +Node 3 (Phys 3): 3355 assigned | 3379 processed | 331 I stole | 307 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1176 chunks (8.7%) +Total Cross-Socket Traffic: 1374 chunks (10.1%) ================================================================= 100000000 -real 0m1.899s -user 0m27.420s -sys 0m21.260s +real 0m1.947s +user 0m27.369s +sys 0m21.511s -CPU UTILIZATION: 25.634 / 28 +CPU UTILIZATION: 25.105 / 28 ----------------------------------------- @@ -3358,19 +3358,19 @@ CPU UTILIZATION: 25.634 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.198s -user 0m6.056s -sys 0m22.765s +real 0m1.221s +user 0m5.989s +sys 0m23.087s -CPU UTILIZATION: 24.057 / 28 +CPU UTILIZATION: 23.813 / 28 ----------------------------------------- @@ -3388,11 +3388,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.202s -user 0m6.041s -sys 0m22.807s +real 0m1.200s +user 0m6.010s +sys 0m23.068s -CPU UTILIZATION: 24.000 / 28 +CPU UTILIZATION: 24.231 / 28 ----------------------------------------- @@ -3401,19 +3401,19 @@ CPU UTILIZATION: 24.000 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3436 assigned | 3440 processed | 162 I stole | 158 stolen from me -Node 1 (Phys 1): 3439 assigned | 3414 processed | 165 I stole | 190 stolen from me -Node 2 (Phys 2): 3305 assigned | 3338 processed | 156 I stole | 123 stolen from me -Node 3 (Phys 3): 3385 assigned | 3373 processed | 157 I stole | 169 stolen from me +Node 0 (Phys 0): 3375 assigned | 3326 processed | 163 I stole | 212 stolen from me +Node 1 (Phys 1): 3438 assigned | 3446 processed | 182 I stole | 174 stolen from me +Node 2 (Phys 2): 3411 assigned | 3437 processed | 191 I stole | 165 stolen from me +Node 3 (Phys 3): 3341 assigned | 3356 processed | 168 I stole | 153 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 640 chunks (4.7%) +Total Cross-Socket Traffic: 704 chunks (5.2%) ================================================================= -real 0m1.342s -user 0m9.091s -sys 0m23.429s +real 0m1.352s +user 0m9.282s +sys 0m23.526s -CPU UTILIZATION: 24.232 / 28 +CPU UTILIZATION: 24.266 / 28 ----------------------------------------- @@ -3422,20 +3422,20 @@ CPU UTILIZATION: 24.232 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3429 assigned | 3423 processed | 159 I stole | 165 stolen from me -Node 1 (Phys 1): 3376 assigned | 3328 processed | 144 I stole | 192 stolen from me -Node 2 (Phys 2): 3351 assigned | 3396 processed | 183 I stole | 138 stolen from me -Node 3 (Phys 3): 3409 assigned | 3418 processed | 168 I stole | 159 stolen from me +Node 0 (Phys 0): 3409 assigned | 3421 processed | 162 I stole | 150 stolen from me +Node 1 (Phys 1): 3405 assigned | 3399 processed | 156 I stole | 162 stolen from me +Node 2 (Phys 2): 3403 assigned | 3401 processed | 155 I stole | 157 stolen from me +Node 3 (Phys 3): 3348 assigned | 3344 processed | 130 I stole | 134 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 654 chunks (4.8%) +Total Cross-Socket Traffic: 603 chunks (4.4%) ================================================================= 0 -real 0m1.337s -user 0m9.156s -sys 0m23.398s +real 0m1.354s +user 0m9.253s +sys 0m23.648s -CPU UTILIZATION: 24.348 / 28 +CPU UTILIZATION: 24.299 / 28 ----------------------------------------- @@ -3445,18 +3445,18 @@ CPU UTILIZATION: 24.348 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.317s -user 0m7.246s -sys 0m24.863s +real 0m1.335s +user 0m7.432s +sys 0m24.908s -CPU UTILIZATION: 24.380 / 28 +CPU UTILIZATION: 24.224 / 28 ----------------------------------------- @@ -3466,19 +3466,19 @@ CPU UTILIZATION: 24.380 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m1.332s -user 0m7.490s -sys 0m25.001s +real 0m1.383s +user 0m7.546s +sys 0m25.250s -CPU UTILIZATION: 24.392 / 28 +CPU UTILIZATION: 23.713 / 28 ----------------------------------------- @@ -3487,19 +3487,19 @@ CPU UTILIZATION: 24.392 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3462 assigned | 3476 processed | 191 I stole | 177 stolen from me -Node 1 (Phys 1): 3465 assigned | 3444 processed | 167 I stole | 188 stolen from me -Node 2 (Phys 2): 3425 assigned | 3445 processed | 180 I stole | 160 stolen from me -Node 3 (Phys 3): 3213 assigned | 3200 processed | 161 I stole | 174 stolen from me +Node 0 (Phys 0): 3409 assigned | 3381 processed | 182 I stole | 210 stolen from me +Node 1 (Phys 1): 3392 assigned | 3383 processed | 188 I stole | 197 stolen from me +Node 2 (Phys 2): 3365 assigned | 3381 processed | 200 I stole | 184 stolen from me +Node 3 (Phys 3): 3399 assigned | 3420 processed | 199 I stole | 178 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 699 chunks (5.2%) +Total Cross-Socket Traffic: 769 chunks (5.7%) ================================================================= -real 0m1.665s -user 0m9.770s -sys 0m26.100s +real 0m1.478s +user 0m9.994s +sys 0m26.197s -CPU UTILIZATION: 21.543 / 28 +CPU UTILIZATION: 24.486 / 28 ----------------------------------------- @@ -3508,20 +3508,20 @@ CPU UTILIZATION: 21.543 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3436 assigned | 3403 processed | 190 I stole | 223 stolen from me -Node 1 (Phys 1): 3397 assigned | 3374 processed | 188 I stole | 211 stolen from me -Node 2 (Phys 2): 3387 assigned | 3414 processed | 206 I stole | 179 stolen from me -Node 3 (Phys 3): 3345 assigned | 3374 processed | 212 I stole | 183 stolen from me +Node 0 (Phys 0): 3426 assigned | 3392 processed | 189 I stole | 223 stolen from me +Node 1 (Phys 1): 3412 assigned | 3399 processed | 192 I stole | 205 stolen from me +Node 2 (Phys 2): 3398 assigned | 3372 processed | 172 I stole | 198 stolen from me +Node 3 (Phys 3): 3329 assigned | 3402 processed | 238 I stole | 165 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 796 chunks (5.9%) +Total Cross-Socket Traffic: 791 chunks (5.8%) ================================================================= 28349 -real 0m1.474s -user 0m9.711s -sys 0m26.474s +real 0m1.483s +user 0m9.981s +sys 0m26.630s -CPU UTILIZATION: 24.548 / 28 +CPU UTILIZATION: 24.687 / 28 ----------------------------------------- @@ -3531,18 +3531,18 @@ CPU UTILIZATION: 24.548 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m2.075s -user 0m27.668s -sys 0m24.709s +real 0m2.080s +user 0m27.580s +sys 0m24.995s -CPU UTILIZATION: 25.241 / 28 +CPU UTILIZATION: 25.276 / 28 ----------------------------------------- @@ -3551,20 +3551,20 @@ CPU UTILIZATION: 25.241 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m2.088s -user 0m27.651s -sys 0m25.178s +real 0m2.095s +user 0m27.667s +sys 0m25.395s -CPU UTILIZATION: 25.301 / 28 +CPU UTILIZATION: 25.327 / 28 ----------------------------------------- @@ -3573,19 +3573,19 @@ CPU UTILIZATION: 25.301 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3413 assigned | 3400 processed | 175 I stole | 188 stolen from me -Node 1 (Phys 1): 3377 assigned | 3386 processed | 166 I stole | 157 stolen from me -Node 2 (Phys 2): 3415 assigned | 3391 processed | 171 I stole | 195 stolen from me -Node 3 (Phys 3): 3360 assigned | 3388 processed | 156 I stole | 128 stolen from me +Node 0 (Phys 0): 3431 assigned | 3406 processed | 209 I stole | 234 stolen from me +Node 1 (Phys 1): 3370 assigned | 3390 processed | 222 I stole | 202 stolen from me +Node 2 (Phys 2): 3389 assigned | 3373 processed | 201 I stole | 217 stolen from me +Node 3 (Phys 3): 3375 assigned | 3396 processed | 188 I stole | 167 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 668 chunks (4.9%) +Total Cross-Socket Traffic: 820 chunks (6.0%) ================================================================= -real 0m2.191s -user 0m29.738s -sys 0m25.986s +real 0m2.204s +user 0m29.851s +sys 0m26.179s -CPU UTILIZATION: 25.433 / 28 +CPU UTILIZATION: 25.421 / 28 ----------------------------------------- @@ -3594,20 +3594,20 @@ CPU UTILIZATION: 25.433 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3386 assigned | 3384 processed | 171 I stole | 173 stolen from me -Node 1 (Phys 1): 3415 assigned | 3408 processed | 165 I stole | 172 stolen from me -Node 2 (Phys 2): 3414 assigned | 3391 processed | 148 I stole | 171 stolen from me -Node 3 (Phys 3): 3350 assigned | 3382 processed | 169 I stole | 137 stolen from me +Node 0 (Phys 0): 3399 assigned | 3410 processed | 200 I stole | 189 stolen from me +Node 1 (Phys 1): 3432 assigned | 3406 processed | 164 I stole | 190 stolen from me +Node 2 (Phys 2): 3388 assigned | 3383 processed | 154 I stole | 159 stolen from me +Node 3 (Phys 3): 3346 assigned | 3366 processed | 178 I stole | 158 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 653 chunks (4.8%) +Total Cross-Socket Traffic: 696 chunks (5.1%) ================================================================= 100000000 -real 0m2.201s -user 0m29.730s -sys 0m26.432s +real 0m2.210s +user 0m29.683s +sys 0m26.780s -CPU UTILIZATION: 25.516 / 28 +CPU UTILIZATION: 25.548 / 28 ----------------------------------------- @@ -3616,19 +3616,19 @@ CPU UTILIZATION: 25.516 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.737s -user 0m1.909s -sys 0m15.560s +user 0m1.945s +sys 0m15.645s -CPU UTILIZATION: 23.702 / 28 +CPU UTILIZATION: 23.867 / 28 ----------------------------------------- @@ -3637,8 +3637,8 @@ CPU UTILIZATION: 23.702 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -3646,11 +3646,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.734s -user 0m1.894s -sys 0m15.640s +real 0m0.735s +user 0m1.895s +sys 0m15.712s -CPU UTILIZATION: 23.888 / 28 +CPU UTILIZATION: 23.955 / 28 ----------------------------------------- @@ -3659,19 +3659,19 @@ CPU UTILIZATION: 23.888 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3389 assigned | 3375 processed | 216 I stole | 230 stolen from me -Node 1 (Phys 1): 3384 assigned | 3375 processed | 204 I stole | 213 stolen from me -Node 2 (Phys 2): 3392 assigned | 3398 processed | 209 I stole | 203 stolen from me -Node 3 (Phys 3): 3400 assigned | 3417 processed | 215 I stole | 198 stolen from me +Node 0 (Phys 0): 3423 assigned | 3448 processed | 285 I stole | 260 stolen from me +Node 1 (Phys 1): 3397 assigned | 3376 processed | 242 I stole | 263 stolen from me +Node 2 (Phys 2): 3404 assigned | 3395 processed | 216 I stole | 225 stolen from me +Node 3 (Phys 3): 3341 assigned | 3346 processed | 244 I stole | 239 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 844 chunks (6.2%) +Total Cross-Socket Traffic: 987 chunks (7.3%) ================================================================= -real 0m1.070s -user 0m4.806s -sys 0m20.223s +real 0m1.074s +user 0m4.793s +sys 0m20.409s -CPU UTILIZATION: 23.391 / 28 +CPU UTILIZATION: 23.465 / 28 ----------------------------------------- @@ -3680,20 +3680,20 @@ CPU UTILIZATION: 23.391 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3422 assigned | 3409 processed | 222 I stole | 235 stolen from me -Node 1 (Phys 1): 3401 assigned | 3386 processed | 204 I stole | 219 stolen from me -Node 2 (Phys 2): 3309 assigned | 3335 processed | 217 I stole | 191 stolen from me -Node 3 (Phys 3): 3433 assigned | 3435 processed | 212 I stole | 210 stolen from me +Node 0 (Phys 0): 3426 assigned | 3425 processed | 184 I stole | 185 stolen from me +Node 1 (Phys 1): 3524 assigned | 3521 processed | 191 I stole | 194 stolen from me +Node 2 (Phys 2): 3412 assigned | 3453 processed | 217 I stole | 176 stolen from me +Node 3 (Phys 3): 3203 assigned | 3166 processed | 176 I stole | 213 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 855 chunks (6.3%) +Total Cross-Socket Traffic: 768 chunks (5.7%) ================================================================= 0 -real 0m1.076s -user 0m4.795s -sys 0m20.211s +real 0m1.381s +user 0m4.867s +sys 0m20.686s -CPU UTILIZATION: 23.239 / 28 +CPU UTILIZATION: 18.503 / 28 ----------------------------------------- @@ -3704,17 +3704,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.828s -user 0m3.423s -sys 0m16.556s +real 0m0.837s +user 0m3.429s +sys 0m16.627s -CPU UTILIZATION: 24.129 / 28 +CPU UTILIZATION: 23.961 / 28 ----------------------------------------- @@ -3725,18 +3725,18 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m0.832s -user 0m3.514s -sys 0m16.836s +real 0m0.841s +user 0m3.535s +sys 0m16.906s -CPU UTILIZATION: 24.459 / 28 +CPU UTILIZATION: 24.305 / 28 ----------------------------------------- @@ -3745,19 +3745,19 @@ CPU UTILIZATION: 24.459 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3423 assigned | 3426 processed | 263 I stole | 260 stolen from me -Node 1 (Phys 1): 3374 assigned | 3381 processed | 250 I stole | 243 stolen from me -Node 2 (Phys 2): 3375 assigned | 3385 processed | 236 I stole | 226 stolen from me -Node 3 (Phys 3): 3393 assigned | 3373 processed | 215 I stole | 235 stolen from me +Node 0 (Phys 0): 3455 assigned | 3453 processed | 257 I stole | 259 stolen from me +Node 1 (Phys 1): 3360 assigned | 3345 processed | 248 I stole | 263 stolen from me +Node 2 (Phys 2): 3343 assigned | 3346 processed | 248 I stole | 245 stolen from me +Node 3 (Phys 3): 3407 assigned | 3421 processed | 227 I stole | 213 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 964 chunks (7.1%) +Total Cross-Socket Traffic: 980 chunks (7.2%) ================================================================= -real 0m1.161s -user 0m6.147s -sys 0m21.607s +real 0m1.179s +user 0m6.184s +sys 0m21.864s -CPU UTILIZATION: 23.905 / 28 +CPU UTILIZATION: 23.789 / 28 ----------------------------------------- @@ -3766,20 +3766,20 @@ CPU UTILIZATION: 23.905 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3456 assigned | 3429 processed | 275 I stole | 302 stolen from me -Node 1 (Phys 1): 3362 assigned | 3331 processed | 272 I stole | 303 stolen from me -Node 2 (Phys 2): 3402 assigned | 3404 processed | 291 I stole | 289 stolen from me -Node 3 (Phys 3): 3345 assigned | 3401 processed | 293 I stole | 237 stolen from me +Node 0 (Phys 0): 3432 assigned | 3385 processed | 262 I stole | 309 stolen from me +Node 1 (Phys 1): 3400 assigned | 3385 processed | 277 I stole | 292 stolen from me +Node 2 (Phys 2): 3351 assigned | 3357 processed | 250 I stole | 244 stolen from me +Node 3 (Phys 3): 3382 assigned | 3438 processed | 261 I stole | 205 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1131 chunks (8.3%) +Total Cross-Socket Traffic: 1050 chunks (7.7%) ================================================================= -14837 -real 0m1.181s -user 0m6.249s -sys 0m21.990s +14836 +real 0m1.195s +user 0m6.293s +sys 0m22.242s -CPU UTILIZATION: 23.911 / 28 +CPU UTILIZATION: 23.878 / 28 ----------------------------------------- @@ -3789,18 +3789,18 @@ CPU UTILIZATION: 23.911 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.596s -user 0m24.228s -sys 0m16.830s +real 0m1.599s +user 0m24.071s +sys 0m16.968s -CPU UTILIZATION: 25.725 / 28 +CPU UTILIZATION: 25.665 / 28 ----------------------------------------- @@ -3811,18 +3811,18 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.607s -user 0m24.206s -sys 0m17.139s +real 0m1.614s +user 0m24.168s +sys 0m17.219s -CPU UTILIZATION: 25.728 / 28 +CPU UTILIZATION: 25.642 / 28 ----------------------------------------- @@ -3831,19 +3831,19 @@ CPU UTILIZATION: 25.728 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3422 assigned | 3418 processed | 336 I stole | 340 stolen from me -Node 1 (Phys 1): 3377 assigned | 3371 processed | 342 I stole | 348 stolen from me -Node 2 (Phys 2): 3394 assigned | 3416 processed | 330 I stole | 308 stolen from me -Node 3 (Phys 3): 3372 assigned | 3360 processed | 310 I stole | 322 stolen from me +Node 0 (Phys 0): 3411 assigned | 3393 processed | 353 I stole | 371 stolen from me +Node 1 (Phys 1): 3426 assigned | 3402 processed | 329 I stole | 353 stolen from me +Node 2 (Phys 2): 3409 assigned | 3365 processed | 323 I stole | 367 stolen from me +Node 3 (Phys 3): 3319 assigned | 3405 processed | 365 I stole | 279 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1318 chunks (9.7%) +Total Cross-Socket Traffic: 1370 chunks (10.1%) ================================================================= -real 0m1.890s -user 0m27.271s -sys 0m20.876s +real 0m1.902s +user 0m27.209s +sys 0m21.178s -CPU UTILIZATION: 25.474 / 28 +CPU UTILIZATION: 25.440 / 28 ----------------------------------------- @@ -3852,20 +3852,20 @@ CPU UTILIZATION: 25.474 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3423 assigned | 3412 processed | 336 I stole | 347 stolen from me -Node 1 (Phys 1): 3444 assigned | 3423 processed | 324 I stole | 345 stolen from me -Node 2 (Phys 2): 3313 assigned | 3332 processed | 349 I stole | 330 stolen from me -Node 3 (Phys 3): 3385 assigned | 3398 processed | 293 I stole | 280 stolen from me +Node 0 (Phys 0): 3372 assigned | 3358 processed | 380 I stole | 394 stolen from me +Node 1 (Phys 1): 3393 assigned | 3411 processed | 405 I stole | 387 stolen from me +Node 2 (Phys 2): 3401 assigned | 3364 processed | 350 I stole | 387 stolen from me +Node 3 (Phys 3): 3399 assigned | 3432 processed | 346 I stole | 313 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1302 chunks (9.6%) +Total Cross-Socket Traffic: 1481 chunks (10.9%) ================================================================= 100000000 -real 0m1.899s -user 0m27.310s -sys 0m21.353s +real 0m1.907s +user 0m27.312s +sys 0m21.565s -CPU UTILIZATION: 25.625 / 28 +CPU UTILIZATION: 25.630 / 28 ----------------------------------------- @@ -3875,18 +3875,18 @@ CPU UTILIZATION: 25.625 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.171s -user 0m5.687s -sys 0m22.447s +real 0m1.179s +user 0m5.690s +sys 0m22.638s -CPU UTILIZATION: 24.025 / 28 +CPU UTILIZATION: 24.027 / 28 ----------------------------------------- @@ -3895,8 +3895,8 @@ CPU UTILIZATION: 24.025 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -3904,11 +3904,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m1.171s -user 0m5.779s -sys 0m22.338s +real 0m1.172s +user 0m5.806s +sys 0m22.440s -CPU UTILIZATION: 24.011 / 28 +CPU UTILIZATION: 24.100 / 28 ----------------------------------------- @@ -3917,19 +3917,19 @@ CPU UTILIZATION: 24.011 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3359 assigned | 3337 processed | 167 I stole | 189 stolen from me -Node 1 (Phys 1): 3438 assigned | 3456 processed | 179 I stole | 161 stolen from me -Node 2 (Phys 2): 3424 assigned | 3391 processed | 151 I stole | 184 stolen from me -Node 3 (Phys 3): 3344 assigned | 3381 processed | 204 I stole | 167 stolen from me +Node 0 (Phys 0): 3410 assigned | 3405 processed | 173 I stole | 178 stolen from me +Node 1 (Phys 1): 3314 assigned | 3292 processed | 153 I stole | 175 stolen from me +Node 2 (Phys 2): 3435 assigned | 3418 processed | 156 I stole | 173 stolen from me +Node 3 (Phys 3): 3406 assigned | 3450 processed | 178 I stole | 134 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 701 chunks (5.2%) +Total Cross-Socket Traffic: 660 chunks (4.9%) ================================================================= -real 0m1.307s -user 0m8.857s -sys 0m22.922s +real 0m1.323s +user 0m8.810s +sys 0m23.223s -CPU UTILIZATION: 24.314 / 28 +CPU UTILIZATION: 24.212 / 28 ----------------------------------------- @@ -3938,20 +3938,20 @@ CPU UTILIZATION: 24.314 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3402 assigned | 3389 processed | 197 I stole | 210 stolen from me -Node 1 (Phys 1): 3405 assigned | 3405 processed | 193 I stole | 193 stolen from me -Node 2 (Phys 2): 3389 assigned | 3374 processed | 162 I stole | 177 stolen from me -Node 3 (Phys 3): 3369 assigned | 3397 processed | 188 I stole | 160 stolen from me +Node 0 (Phys 0): 3410 assigned | 3408 processed | 185 I stole | 187 stolen from me +Node 1 (Phys 1): 3328 assigned | 3282 processed | 167 I stole | 213 stolen from me +Node 2 (Phys 2): 3378 assigned | 3410 processed | 190 I stole | 158 stolen from me +Node 3 (Phys 3): 3449 assigned | 3465 processed | 183 I stole | 167 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 740 chunks (5.5%) +Total Cross-Socket Traffic: 725 chunks (5.3%) ================================================================= 0 -real 0m1.315s -user 0m8.803s -sys 0m23.005s +real 0m1.326s +user 0m8.747s +sys 0m23.365s -CPU UTILIZATION: 24.188 / 28 +CPU UTILIZATION: 24.217 / 28 ----------------------------------------- @@ -3960,19 +3960,19 @@ CPU UTILIZATION: 24.188 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.260s -user 0m6.739s -sys 0m23.804s +real 0m1.266s +user 0m6.914s +sys 0m23.887s -CPU UTILIZATION: 24.240 / 28 +CPU UTILIZATION: 24.329 / 28 ----------------------------------------- @@ -3990,11 +3990,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m1.364s -user 0m7.468s -sys 0m23.768s +real 0m1.377s +user 0m7.541s +sys 0m24.024s -CPU UTILIZATION: 22.900 / 28 +CPU UTILIZATION: 22.923 / 28 ----------------------------------------- @@ -4003,19 +4003,19 @@ CPU UTILIZATION: 22.900 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3403 assigned | 3407 processed | 206 I stole | 202 stolen from me -Node 1 (Phys 1): 3419 assigned | 3413 processed | 190 I stole | 196 stolen from me -Node 2 (Phys 2): 3338 assigned | 3325 processed | 190 I stole | 203 stolen from me -Node 3 (Phys 3): 3405 assigned | 3420 processed | 191 I stole | 176 stolen from me +Node 0 (Phys 0): 3416 assigned | 3390 processed | 172 I stole | 198 stolen from me +Node 1 (Phys 1): 3462 assigned | 3417 processed | 149 I stole | 194 stolen from me +Node 2 (Phys 2): 3363 assigned | 3371 processed | 164 I stole | 156 stolen from me +Node 3 (Phys 3): 3324 assigned | 3387 processed | 200 I stole | 137 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 777 chunks (5.7%) +Total Cross-Socket Traffic: 685 chunks (5.0%) ================================================================= -real 0m1.395s -user 0m9.665s -sys 0m24.387s +real 0m1.414s +user 0m9.579s +sys 0m24.945s -CPU UTILIZATION: 24.410 / 28 +CPU UTILIZATION: 24.415 / 28 ----------------------------------------- @@ -4024,20 +4024,20 @@ CPU UTILIZATION: 24.410 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3432 assigned | 3411 processed | 75 I stole | 96 stolen from me -Node 1 (Phys 1): 3389 assigned | 3396 processed | 81 I stole | 74 stolen from me -Node 2 (Phys 2): 3376 assigned | 3379 processed | 69 I stole | 66 stolen from me -Node 3 (Phys 3): 3368 assigned | 3379 processed | 81 I stole | 70 stolen from me +Node 0 (Phys 0): 3375 assigned | 3386 processed | 95 I stole | 84 stolen from me +Node 1 (Phys 1): 3390 assigned | 3393 processed | 91 I stole | 88 stolen from me +Node 2 (Phys 2): 3416 assigned | 3389 processed | 66 I stole | 93 stolen from me +Node 3 (Phys 3): 3384 assigned | 3397 processed | 78 I stole | 65 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 306 chunks (2.3%) +Total Cross-Socket Traffic: 330 chunks (2.4%) ================================================================= -28348 -real 0m1.478s -user 0m9.623s -sys 0m24.722s +28350 +real 0m1.483s +user 0m9.546s +sys 0m25.123s -CPU UTILIZATION: 23.237 / 28 +CPU UTILIZATION: 23.377 / 28 ----------------------------------------- @@ -4046,19 +4046,19 @@ CPU UTILIZATION: 23.237 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m2.014s -user 0m27.235s -sys 0m23.605s +real 0m2.015s +user 0m27.280s +sys 0m23.589s -CPU UTILIZATION: 25.243 / 28 +CPU UTILIZATION: 25.245 / 28 ----------------------------------------- @@ -4076,11 +4076,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m2.224s -user 0m25.133s -sys 0m25.362s +real 0m2.232s +user 0m25.217s +sys 0m25.284s -CPU UTILIZATION: 22.704 / 28 +CPU UTILIZATION: 22.625 / 28 ----------------------------------------- @@ -4089,19 +4089,19 @@ CPU UTILIZATION: 22.704 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3396 assigned | 3409 processed | 179 I stole | 166 stolen from me -Node 1 (Phys 1): 3411 assigned | 3393 processed | 160 I stole | 178 stolen from me -Node 2 (Phys 2): 3394 assigned | 3395 processed | 156 I stole | 155 stolen from me -Node 3 (Phys 3): 3364 assigned | 3368 processed | 156 I stole | 152 stolen from me +Node 0 (Phys 0): 3413 assigned | 3393 processed | 213 I stole | 233 stolen from me +Node 1 (Phys 1): 3407 assigned | 3399 processed | 174 I stole | 182 stolen from me +Node 2 (Phys 2): 3372 assigned | 3385 processed | 191 I stole | 178 stolen from me +Node 3 (Phys 3): 3373 assigned | 3388 processed | 191 I stole | 176 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 651 chunks (4.8%) +Total Cross-Socket Traffic: 769 chunks (5.7%) ================================================================= -real 0m2.128s -user 0m29.168s -sys 0m24.799s +real 0m2.140s +user 0m29.077s +sys 0m25.250s -CPU UTILIZATION: 25.360 / 28 +CPU UTILIZATION: 25.386 / 28 ----------------------------------------- @@ -4110,20 +4110,20 @@ CPU UTILIZATION: 25.360 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3411 assigned | 3402 processed | 14 I stole | 23 stolen from me -Node 1 (Phys 1): 3412 assigned | 3403 processed | 14 I stole | 23 stolen from me -Node 2 (Phys 2): 3375 assigned | 3381 processed | 18 I stole | 12 stolen from me -Node 3 (Phys 3): 3367 assigned | 3379 processed | 25 I stole | 13 stolen from me +Node 0 (Phys 0): 3405 assigned | 3405 processed | 19 I stole | 19 stolen from me +Node 1 (Phys 1): 3408 assigned | 3398 processed | 16 I stole | 26 stolen from me +Node 2 (Phys 2): 3363 assigned | 3370 processed | 18 I stole | 11 stolen from me +Node 3 (Phys 3): 3389 assigned | 3392 processed | 21 I stole | 18 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 71 chunks (0.5%) +Total Cross-Socket Traffic: 74 chunks (0.5%) ================================================================= 100000000 -real 0m2.330s -user 0m26.787s -sys 0m26.719s +real 0m2.344s +user 0m26.830s +sys 0m26.918s -CPU UTILIZATION: 22.963 / 28 +CPU UTILIZATION: 22.930 / 28 ----------------------------------------- @@ -4132,19 +4132,19 @@ CPU UTILIZATION: 22.963 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.736s -user 0m1.837s -sys 0m15.585s +real 0m0.732s +user 0m1.825s +sys 0m15.584s -CPU UTILIZATION: 23.671 / 28 +CPU UTILIZATION: 23.782 / 28 ----------------------------------------- @@ -4154,19 +4154,19 @@ CPU UTILIZATION: 23.671 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 real 0m0.732s -user 0m1.800s -sys 0m15.623s +user 0m1.824s +sys 0m15.593s -CPU UTILIZATION: 23.801 / 28 +CPU UTILIZATION: 23.793 / 28 ----------------------------------------- @@ -4175,19 +4175,19 @@ CPU UTILIZATION: 23.801 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3438 assigned | 3391 processed | 196 I stole | 243 stolen from me -Node 1 (Phys 1): 3423 assigned | 3459 processed | 252 I stole | 216 stolen from me -Node 2 (Phys 2): 3352 assigned | 3330 processed | 210 I stole | 232 stolen from me -Node 3 (Phys 3): 3352 assigned | 3385 processed | 224 I stole | 191 stolen from me +Node 0 (Phys 0): 3378 assigned | 3386 processed | 287 I stole | 279 stolen from me +Node 1 (Phys 1): 3453 assigned | 3360 processed | 239 I stole | 332 stolen from me +Node 2 (Phys 2): 3411 assigned | 3468 processed | 309 I stole | 252 stolen from me +Node 3 (Phys 3): 3323 assigned | 3351 processed | 293 I stole | 265 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 882 chunks (6.5%) +Total Cross-Socket Traffic: 1128 chunks (8.3%) ================================================================= -real 0m1.048s -user 0m4.550s -sys 0m20.010s +real 0m1.047s +user 0m4.571s +sys 0m20.148s -CPU UTILIZATION: 23.435 / 28 +CPU UTILIZATION: 23.609 / 28 ----------------------------------------- @@ -4196,20 +4196,20 @@ CPU UTILIZATION: 23.435 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3387 assigned | 3363 processed | 217 I stole | 241 stolen from me -Node 1 (Phys 1): 3477 assigned | 3483 processed | 253 I stole | 247 stolen from me -Node 2 (Phys 2): 3314 assigned | 3298 processed | 232 I stole | 248 stolen from me -Node 3 (Phys 3): 3387 assigned | 3421 processed | 247 I stole | 213 stolen from me +Node 0 (Phys 0): 3408 assigned | 3404 processed | 288 I stole | 292 stolen from me +Node 1 (Phys 1): 3417 assigned | 3444 processed | 278 I stole | 251 stolen from me +Node 2 (Phys 2): 3389 assigned | 3355 processed | 243 I stole | 277 stolen from me +Node 3 (Phys 3): 3351 assigned | 3362 processed | 244 I stole | 233 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 949 chunks (7.0%) +Total Cross-Socket Traffic: 1053 chunks (7.8%) ================================================================= 0 -real 0m1.077s -user 0m4.468s -sys 0m20.302s +real 0m1.049s +user 0m4.544s +sys 0m20.218s -CPU UTILIZATION: 22.999 / 28 +CPU UTILIZATION: 23.605 / 28 ----------------------------------------- @@ -4218,19 +4218,19 @@ CPU UTILIZATION: 22.999 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.801s +real 0m0.799s user 0m3.354s -sys 0m15.822s +sys 0m15.929s -CPU UTILIZATION: 23.940 / 28 +CPU UTILIZATION: 24.133 / 28 ----------------------------------------- @@ -4248,11 +4248,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m0.878s -user 0m3.329s -sys 0m16.890s +real 0m0.879s +user 0m3.273s +sys 0m17.228s -CPU UTILIZATION: 23.028 / 28 +CPU UTILIZATION: 23.323 / 28 ----------------------------------------- @@ -4261,19 +4261,19 @@ CPU UTILIZATION: 23.028 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3438 assigned | 3413 processed | 248 I stole | 273 stolen from me -Node 1 (Phys 1): 3393 assigned | 3383 processed | 234 I stole | 244 stolen from me -Node 2 (Phys 2): 3401 assigned | 3364 processed | 186 I stole | 223 stolen from me -Node 3 (Phys 3): 3333 assigned | 3405 processed | 258 I stole | 186 stolen from me +Node 0 (Phys 0): 3446 assigned | 3445 processed | 289 I stole | 290 stolen from me +Node 1 (Phys 1): 3349 assigned | 3332 processed | 272 I stole | 289 stolen from me +Node 2 (Phys 2): 3429 assigned | 3398 processed | 246 I stole | 277 stolen from me +Node 3 (Phys 3): 3341 assigned | 3390 processed | 271 I stole | 222 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 926 chunks (6.8%) +Total Cross-Socket Traffic: 1078 chunks (7.9%) ================================================================= -real 0m1.145s -user 0m5.793s -sys 0m20.814s +real 0m1.136s +user 0m5.842s +sys 0m20.940s -CPU UTILIZATION: 23.237 / 28 +CPU UTILIZATION: 23.575 / 28 ----------------------------------------- @@ -4282,20 +4282,20 @@ CPU UTILIZATION: 23.237 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3440 assigned | 3442 processed | 212 I stole | 210 stolen from me -Node 1 (Phys 1): 3344 assigned | 3287 processed | 187 I stole | 244 stolen from me -Node 2 (Phys 2): 3357 assigned | 3412 processed | 215 I stole | 160 stolen from me -Node 3 (Phys 3): 3424 assigned | 3424 processed | 179 I stole | 179 stolen from me +Node 0 (Phys 0): 3450 assigned | 3456 processed | 190 I stole | 184 stolen from me +Node 1 (Phys 1): 3399 assigned | 3386 processed | 168 I stole | 181 stolen from me +Node 2 (Phys 2): 3326 assigned | 3336 processed | 167 I stole | 157 stolen from me +Node 3 (Phys 3): 3390 assigned | 3387 processed | 145 I stole | 148 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 793 chunks (5.8%) +Total Cross-Socket Traffic: 670 chunks (4.9%) ================================================================= -14836 +14835 real 0m1.194s -user 0m5.624s -sys 0m21.697s +user 0m5.780s +sys 0m21.798s -CPU UTILIZATION: 22.881 / 28 +CPU UTILIZATION: 23.097 / 28 ----------------------------------------- @@ -4304,8 +4304,8 @@ CPU UTILIZATION: 22.881 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -4313,10 +4313,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m1.568s -user 0m24.180s -sys 0m16.067s +user 0m24.162s +sys 0m16.128s -CPU UTILIZATION: 25.667 / 28 +CPU UTILIZATION: 25.695 / 28 ----------------------------------------- @@ -4334,11 +4334,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m1.708s -user 0m22.309s -sys 0m16.035s +real 0m1.706s +user 0m22.317s +sys 0m16.015s -CPU UTILIZATION: 22.449 / 28 +CPU UTILIZATION: 22.468 / 28 ----------------------------------------- @@ -4347,19 +4347,19 @@ CPU UTILIZATION: 22.449 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3398 assigned | 3368 processed | 316 I stole | 346 stolen from me -Node 1 (Phys 1): 3372 assigned | 3410 processed | 357 I stole | 319 stolen from me -Node 2 (Phys 2): 3403 assigned | 3411 processed | 311 I stole | 303 stolen from me -Node 3 (Phys 3): 3392 assigned | 3376 processed | 275 I stole | 291 stolen from me +Node 0 (Phys 0): 3372 assigned | 3378 processed | 361 I stole | 355 stolen from me +Node 1 (Phys 1): 3454 assigned | 3424 processed | 341 I stole | 371 stolen from me +Node 2 (Phys 2): 3382 assigned | 3396 processed | 345 I stole | 331 stolen from me +Node 3 (Phys 3): 3357 assigned | 3367 processed | 334 I stole | 324 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1259 chunks (9.3%) +Total Cross-Socket Traffic: 1381 chunks (10.2%) ================================================================= -real 0m1.845s -user 0m26.826s -sys 0m20.100s +real 0m1.855s +user 0m26.843s +sys 0m20.289s -CPU UTILIZATION: 25.434 / 28 +CPU UTILIZATION: 25.408 / 28 ----------------------------------------- @@ -4368,20 +4368,20 @@ CPU UTILIZATION: 25.434 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3445 assigned | 3406 processed | 104 I stole | 143 stolen from me -Node 1 (Phys 1): 3374 assigned | 3382 processed | 120 I stole | 112 stolen from me -Node 2 (Phys 2): 3393 assigned | 3412 processed | 120 I stole | 101 stolen from me -Node 3 (Phys 3): 3353 assigned | 3365 processed | 105 I stole | 93 stolen from me +Node 0 (Phys 0): 3406 assigned | 3412 processed | 132 I stole | 126 stolen from me +Node 1 (Phys 1): 3366 assigned | 3374 processed | 99 I stole | 91 stolen from me +Node 2 (Phys 2): 3406 assigned | 3385 processed | 79 I stole | 100 stolen from me +Node 3 (Phys 3): 3387 assigned | 3394 processed | 84 I stole | 77 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 449 chunks (3.3%) +Total Cross-Socket Traffic: 394 chunks (2.9%) ================================================================= 100000000 -real 0m2.060s -user 0m24.867s -sys 0m21.342s +real 0m2.063s +user 0m24.849s +sys 0m21.479s -CPU UTILIZATION: 22.431 / 28 +CPU UTILIZATION: 22.456 / 28 ----------------------------------------- @@ -4390,19 +4390,19 @@ CPU UTILIZATION: 22.431 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 103 assigned | 103 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m4.296s -user 1m55.127s -sys 0m1.746s +real 0m4.307s +user 1m55.423s +sys 0m1.773s -CPU UTILIZATION: 27.205 / 28 +CPU UTILIZATION: 27.210 / 28 ----------------------------------------- @@ -4411,20 +4411,20 @@ CPU UTILIZATION: 27.205 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 104 assigned | 104 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 109 assigned | 109 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m4.292s -user 1m55.211s -sys 0m1.766s +real 0m4.307s +user 1m54.847s +sys 0m1.809s -CPU UTILIZATION: 27.254 / 28 +CPU UTILIZATION: 27.085 / 28 ----------------------------------------- @@ -4433,19 +4433,19 @@ CPU UTILIZATION: 27.254 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3437 assigned | 3433 processed | 56 I stole | 60 stolen from me -Node 1 (Phys 1): 3379 assigned | 3371 processed | 50 I stole | 58 stolen from me -Node 2 (Phys 2): 3413 assigned | 3424 processed | 64 I stole | 53 stolen from me -Node 3 (Phys 3): 3336 assigned | 3337 processed | 48 I stole | 47 stolen from me +Node 0 (Phys 0): 3239 assigned | 3244 processed | 9 I stole | 4 stolen from me +Node 1 (Phys 1): 3456 assigned | 3458 processed | 6 I stole | 4 stolen from me +Node 2 (Phys 2): 3462 assigned | 3460 processed | 1 I stole | 3 stolen from me +Node 3 (Phys 3): 3408 assigned | 3403 processed | 1 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 218 chunks (1.6%) +Total Cross-Socket Traffic: 17 chunks (0.1%) ================================================================= -real 0m4.403s -user 1m56.548s -sys 0m2.468s +real 0m4.397s +user 1m57.349s +sys 0m2.445s -CPU UTILIZATION: 27.030 / 28 +CPU UTILIZATION: 27.244 / 28 ----------------------------------------- @@ -4454,20 +4454,20 @@ CPU UTILIZATION: 27.030 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3417 assigned | 3412 processed | 16 I stole | 21 stolen from me -Node 1 (Phys 1): 3371 assigned | 3383 processed | 28 I stole | 16 stolen from me -Node 2 (Phys 2): 3440 assigned | 3441 processed | 20 I stole | 19 stolen from me -Node 3 (Phys 3): 3337 assigned | 3329 processed | 13 I stole | 21 stolen from me +Node 0 (Phys 0): 3432 assigned | 3434 processed | 3 I stole | 1 stolen from me +Node 1 (Phys 1): 3351 assigned | 3350 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 3506 assigned | 3506 processed | 1 I stole | 1 stolen from me +Node 3 (Phys 3): 3276 assigned | 3275 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 77 chunks (0.6%) +Total Cross-Socket Traffic: 6 chunks (0.0%) ================================================================= 0 -real 0m4.391s -user 1m57.146s -sys 0m2.405s +real 0m4.414s +user 1m58.044s +sys 0m2.375s -CPU UTILIZATION: 27.226 / 28 +CPU UTILIZATION: 27.281 / 28 ----------------------------------------- @@ -4477,18 +4477,18 @@ CPU UTILIZATION: 27.226 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m4.735s -user 2m6.250s -sys 0m2.560s +real 0m4.737s +user 2m6.393s +sys 0m2.662s -CPU UTILIZATION: 27.203 / 28 +CPU UTILIZATION: 27.244 / 28 ----------------------------------------- @@ -4497,20 +4497,20 @@ CPU UTILIZATION: 27.203 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 109 assigned | 109 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 100 assigned | 100 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 25597 -real 0m4.766s -user 2m6.772s -sys 0m2.701s +real 0m4.740s +user 2m6.261s +sys 0m2.845s -CPU UTILIZATION: 27.165 / 28 +CPU UTILIZATION: 27.237 / 28 ----------------------------------------- @@ -4519,19 +4519,19 @@ CPU UTILIZATION: 27.165 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3451 assigned | 3440 processed | 15 I stole | 26 stolen from me -Node 1 (Phys 1): 3410 assigned | 3423 processed | 25 I stole | 12 stolen from me -Node 2 (Phys 2): 3377 assigned | 3384 processed | 18 I stole | 11 stolen from me -Node 3 (Phys 3): 3327 assigned | 3318 processed | 7 I stole | 16 stolen from me +Node 0 (Phys 0): 3343 assigned | 3352 processed | 34 I stole | 25 stolen from me +Node 1 (Phys 1): 3410 assigned | 3404 processed | 18 I stole | 24 stolen from me +Node 2 (Phys 2): 3462 assigned | 3461 processed | 17 I stole | 18 stolen from me +Node 3 (Phys 3): 3350 assigned | 3348 processed | 18 I stole | 20 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 65 chunks (0.5%) +Total Cross-Socket Traffic: 87 chunks (0.6%) ================================================================= -real 0m4.829s -user 2m8.417s -sys 0m3.200s +real 0m4.843s +user 2m8.738s +sys 0m3.372s -CPU UTILIZATION: 27.255 / 28 +CPU UTILIZATION: 27.278 / 28 ----------------------------------------- @@ -4540,20 +4540,20 @@ CPU UTILIZATION: 27.255 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3407 assigned | 3406 processed | 3 I stole | 4 stolen from me -Node 1 (Phys 1): 3451 assigned | 3453 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 3246 assigned | 3244 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 3461 assigned | 3462 processed | 4 I stole | 3 stolen from me +Node 0 (Phys 0): 3380 assigned | 3380 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 3509 assigned | 3509 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 3506 assigned | 3506 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 3170 assigned | 3170 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 13 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -28349 -real 0m4.832s -user 2m8.748s -sys 0m3.333s +28350 +real 0m4.863s +user 2m9.372s +sys 0m3.501s -CPU UTILIZATION: 27.334 / 28 +CPU UTILIZATION: 27.323 / 28 ----------------------------------------- @@ -4563,18 +4563,18 @@ CPU UTILIZATION: 27.334 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m8.073s -user 2m49.406s -sys 0m51.269s +real 0m8.251s +user 2m53.146s +sys 0m52.966s -CPU UTILIZATION: 27.334 / 28 +CPU UTILIZATION: 27.404 / 28 ----------------------------------------- @@ -4583,8 +4583,8 @@ CPU UTILIZATION: 27.334 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -4592,11 +4592,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m8.080s -user 2m49.521s -sys 0m52.184s +real 0m8.199s +user 2m51.144s +sys 0m53.189s -CPU UTILIZATION: 27.438 / 28 +CPU UTILIZATION: 27.361 / 28 ----------------------------------------- @@ -4605,19 +4605,19 @@ CPU UTILIZATION: 27.438 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3340 assigned | 3341 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 3398 assigned | 3397 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 3416 assigned | 3416 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3411 assigned | 3411 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 3451 assigned | 3454 processed | 3 I stole | 0 stolen from me +Node 1 (Phys 1): 3385 assigned | 3383 processed | 0 I stole | 2 stolen from me +Node 2 (Phys 2): 3438 assigned | 3437 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 3291 assigned | 3291 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.0%) ================================================================= -real 0m8.169s -user 2m52.570s -sys 0m52.179s +real 0m8.263s +user 2m53.561s +sys 0m53.514s -CPU UTILIZATION: 27.512 / 28 +CPU UTILIZATION: 27.480 / 28 ----------------------------------------- @@ -4626,20 +4626,20 @@ CPU UTILIZATION: 27.512 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3366 assigned | 3367 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 3448 assigned | 3447 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 3362 assigned | 3362 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3389 assigned | 3389 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 3482 assigned | 3483 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 3323 assigned | 3323 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 3306 assigned | 3305 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 3454 assigned | 3454 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.0%) ================================================================= 100000000 -real 0m8.196s -user 2m52.546s -sys 0m52.923s +real 0m8.252s +user 2m52.989s +sys 0m54.012s -CPU UTILIZATION: 27.509 / 28 +CPU UTILIZATION: 27.508 / 28 ----------------------------------------- @@ -4648,19 +4648,19 @@ CPU UTILIZATION: 27.509 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m4.679s -user 2m4.680s -sys 0m1.663s +real 0m4.653s +user 2m4.330s +sys 0m1.668s -CPU UTILIZATION: 27.002 / 28 +CPU UTILIZATION: 27.078 / 28 ----------------------------------------- @@ -4669,20 +4669,20 @@ CPU UTILIZATION: 27.002 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m4.643s -user 2m3.766s -sys 0m1.604s +real 0m4.677s +user 2m4.641s +sys 0m1.651s -CPU UTILIZATION: 27.001 / 28 +CPU UTILIZATION: 27.002 / 28 ----------------------------------------- @@ -4691,19 +4691,19 @@ CPU UTILIZATION: 27.001 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3378 assigned | 3410 processed | 80 I stole | 48 stolen from me -Node 1 (Phys 1): 3400 assigned | 3385 processed | 42 I stole | 57 stolen from me -Node 2 (Phys 2): 3460 assigned | 3465 processed | 57 I stole | 52 stolen from me -Node 3 (Phys 3): 3327 assigned | 3305 processed | 40 I stole | 62 stolen from me +Node 0 (Phys 0): 3401 assigned | 3399 processed | 61 I stole | 63 stolen from me +Node 1 (Phys 1): 3420 assigned | 3401 processed | 47 I stole | 66 stolen from me +Node 2 (Phys 2): 3364 assigned | 3381 processed | 56 I stole | 39 stolen from me +Node 3 (Phys 3): 3380 assigned | 3384 processed | 43 I stole | 39 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 219 chunks (1.6%) +Total Cross-Socket Traffic: 207 chunks (1.5%) ================================================================= -real 0m4.378s -user 1m56.787s -sys 0m2.200s +real 0m4.397s +user 1m57.185s +sys 0m2.236s -CPU UTILIZATION: 27.178 / 28 +CPU UTILIZATION: 27.159 / 28 ----------------------------------------- @@ -4712,20 +4712,20 @@ CPU UTILIZATION: 27.178 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3343 assigned | 3341 processed | 88 I stole | 90 stolen from me -Node 1 (Phys 1): 3460 assigned | 3468 processed | 90 I stole | 82 stolen from me -Node 2 (Phys 2): 3389 assigned | 3383 processed | 67 I stole | 73 stolen from me -Node 3 (Phys 3): 3373 assigned | 3373 processed | 63 I stole | 63 stolen from me +Node 0 (Phys 0): 3405 assigned | 3378 processed | 57 I stole | 84 stolen from me +Node 1 (Phys 1): 3374 assigned | 3370 processed | 73 I stole | 77 stolen from me +Node 2 (Phys 2): 3436 assigned | 3455 processed | 59 I stole | 40 stolen from me +Node 3 (Phys 3): 3350 assigned | 3362 processed | 79 I stole | 67 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 308 chunks (2.3%) +Total Cross-Socket Traffic: 268 chunks (2.0%) ================================================================= 0 -real 0m4.382s -user 1m56.774s -sys 0m2.186s +real 0m4.392s +user 1m56.734s +sys 0m2.241s -CPU UTILIZATION: 27.147 / 28 +CPU UTILIZATION: 27.089 / 28 ----------------------------------------- @@ -4734,19 +4734,19 @@ CPU UTILIZATION: 27.147 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m5.031s -user 2m14.167s -sys 0m2.369s +real 0m5.038s +user 2m14.129s +sys 0m2.400s -CPU UTILIZATION: 27.138 / 28 +CPU UTILIZATION: 27.099 / 28 ----------------------------------------- @@ -4755,20 +4755,20 @@ CPU UTILIZATION: 27.138 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 4860 -real 0m5.042s -user 2m13.884s -sys 0m2.593s +real 0m5.059s +user 2m14.319s +sys 0m2.810s -CPU UTILIZATION: 27.068 / 28 +CPU UTILIZATION: 27.105 / 28 ----------------------------------------- @@ -4777,19 +4777,19 @@ CPU UTILIZATION: 27.068 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3371 assigned | 3388 processed | 48 I stole | 31 stolen from me -Node 1 (Phys 1): 3417 assigned | 3394 processed | 23 I stole | 46 stolen from me -Node 2 (Phys 2): 3439 assigned | 3442 processed | 38 I stole | 35 stolen from me -Node 3 (Phys 3): 3338 assigned | 3341 processed | 34 I stole | 31 stolen from me +Node 0 (Phys 0): 3403 assigned | 3391 processed | 78 I stole | 90 stolen from me +Node 1 (Phys 1): 3435 assigned | 3422 processed | 75 I stole | 88 stolen from me +Node 2 (Phys 2): 3458 assigned | 3473 processed | 104 I stole | 89 stolen from me +Node 3 (Phys 3): 3269 assigned | 3279 processed | 82 I stole | 72 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 143 chunks (1.1%) +Total Cross-Socket Traffic: 339 chunks (2.5%) ================================================================= -real 0m4.822s -user 2m8.086s -sys 0m3.046s +real 0m4.836s +user 2m7.843s +sys 0m3.057s -CPU UTILIZATION: 27.194 / 28 +CPU UTILIZATION: 27.067 / 28 ----------------------------------------- @@ -4798,20 +4798,20 @@ CPU UTILIZATION: 27.194 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3437 assigned | 3422 processed | 52 I stole | 67 stolen from me -Node 1 (Phys 1): 3355 assigned | 3376 processed | 64 I stole | 43 stolen from me -Node 2 (Phys 2): 3459 assigned | 3438 processed | 47 I stole | 68 stolen from me -Node 3 (Phys 3): 3314 assigned | 3329 processed | 53 I stole | 38 stolen from me +Node 0 (Phys 0): 3448 assigned | 3446 processed | 38 I stole | 40 stolen from me +Node 1 (Phys 1): 3418 assigned | 3415 processed | 46 I stole | 49 stolen from me +Node 2 (Phys 2): 3295 assigned | 3307 processed | 46 I stole | 34 stolen from me +Node 3 (Phys 3): 3404 assigned | 3397 processed | 40 I stole | 47 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 216 chunks (1.6%) +Total Cross-Socket Traffic: 170 chunks (1.3%) ================================================================= -14836 -real 0m4.822s -user 2m8.020s -sys 0m3.200s +14835 +real 0m4.844s +user 2m8.286s +sys 0m3.300s -CPU UTILIZATION: 27.212 / 28 +CPU UTILIZATION: 27.164 / 28 ----------------------------------------- @@ -4820,19 +4820,19 @@ CPU UTILIZATION: 27.212 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 104 assigned | 104 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m8.277s -user 2m54.009s -sys 0m52.310s +real 0m8.289s +user 2m55.714s +sys 0m50.142s -CPU UTILIZATION: 27.343 / 28 +CPU UTILIZATION: 27.247 / 28 ----------------------------------------- @@ -4841,20 +4841,20 @@ CPU UTILIZATION: 27.343 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 108 assigned | 108 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m8.308s -user 2m55.040s -sys 0m51.493s +real 0m8.291s +user 2m55.252s +sys 0m51.302s -CPU UTILIZATION: 27.266 / 28 +CPU UTILIZATION: 27.325 / 28 ----------------------------------------- @@ -4863,19 +4863,19 @@ CPU UTILIZATION: 27.266 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3377 assigned | 3385 processed | 27 I stole | 19 stolen from me -Node 1 (Phys 1): 3398 assigned | 3386 processed | 16 I stole | 28 stolen from me -Node 2 (Phys 2): 3359 assigned | 3357 processed | 18 I stole | 20 stolen from me -Node 3 (Phys 3): 3431 assigned | 3437 processed | 27 I stole | 21 stolen from me +Node 0 (Phys 0): 3465 assigned | 3447 processed | 25 I stole | 43 stolen from me +Node 1 (Phys 1): 3392 assigned | 3394 processed | 41 I stole | 39 stolen from me +Node 2 (Phys 2): 3362 assigned | 3376 processed | 38 I stole | 24 stolen from me +Node 3 (Phys 3): 3346 assigned | 3348 processed | 37 I stole | 35 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 88 chunks (0.6%) +Total Cross-Socket Traffic: 141 chunks (1.0%) ================================================================= -real 0m8.141s -user 2m51.599s -sys 0m52.063s +real 0m8.206s +user 2m53.318s +sys 0m51.899s -CPU UTILIZATION: 27.473 / 28 +CPU UTILIZATION: 27.445 / 28 ----------------------------------------- @@ -4884,20 +4884,20 @@ CPU UTILIZATION: 27.473 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3347 assigned | 3331 processed | 24 I stole | 40 stolen from me -Node 1 (Phys 1): 3478 assigned | 3476 processed | 28 I stole | 30 stolen from me -Node 2 (Phys 2): 3398 assigned | 3404 processed | 30 I stole | 24 stolen from me -Node 3 (Phys 3): 3342 assigned | 3354 processed | 27 I stole | 15 stolen from me +Node 0 (Phys 0): 3419 assigned | 3418 processed | 25 I stole | 26 stolen from me +Node 1 (Phys 1): 3314 assigned | 3321 processed | 27 I stole | 20 stolen from me +Node 2 (Phys 2): 3465 assigned | 3465 processed | 24 I stole | 24 stolen from me +Node 3 (Phys 3): 3367 assigned | 3361 processed | 17 I stole | 23 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 109 chunks (0.8%) +Total Cross-Socket Traffic: 93 chunks (0.7%) ================================================================= 100000000 -real 0m8.243s -user 2m53.318s -sys 0m53.311s +real 0m8.212s +user 2m52.964s +sys 0m52.710s -CPU UTILIZATION: 27.493 / 28 +CPU UTILIZATION: 27.481 / 28 ----------------------------------------- @@ -4906,19 +4906,19 @@ CPU UTILIZATION: 27.493 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (0.2%) ================================================================= -real 0m0.404s -user 0m1.346s -sys 0m1.387s +real 0m0.414s +user 0m1.336s +sys 0m1.421s -CPU UTILIZATION: 6.764 / 28 +CPU UTILIZATION: 6.659 / 28 ----------------------------------------- @@ -4936,11 +4936,11 @@ Total Cross-Socket Traffic: 1 chunks (0.2%) ================================================================= 0 -real 0m0.404s -user 0m1.485s -sys 0m1.365s +real 0m0.407s +user 0m1.300s +sys 0m1.418s -CPU UTILIZATION: 7.054 / 28 +CPU UTILIZATION: 6.678 / 28 ----------------------------------------- @@ -4949,17 +4949,17 @@ CPU UTILIZATION: 7.054 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3401 assigned | 3410 processed | 9 I stole | 0 stolen from me -Node 1 (Phys 1): 3403 assigned | 3405 processed | 5 I stole | 3 stolen from me -Node 2 (Phys 2): 3376 assigned | 3368 processed | 0 I stole | 8 stolen from me -Node 3 (Phys 3): 3385 assigned | 3382 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 3385 assigned | 3391 processed | 6 I stole | 0 stolen from me +Node 1 (Phys 1): 3398 assigned | 3405 processed | 8 I stole | 1 stolen from me +Node 2 (Phys 2): 3397 assigned | 3390 processed | 1 I stole | 8 stolen from me +Node 3 (Phys 3): 3385 assigned | 3379 processed | 0 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 14 chunks (0.1%) +Total Cross-Socket Traffic: 15 chunks (0.1%) ================================================================= -real 0m0.550s -user 0m3.996s -sys 0m3.503s +real 0m0.564s +user 0m4.027s +sys 0m3.663s CPU UTILIZATION: 13.634 / 28 @@ -4970,20 +4970,20 @@ CPU UTILIZATION: 13.634 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3399 assigned | 3414 processed | 18 I stole | 3 stolen from me -Node 1 (Phys 1): 3394 assigned | 3387 processed | 2 I stole | 9 stolen from me -Node 2 (Phys 2): 3385 assigned | 3375 processed | 2 I stole | 12 stolen from me -Node 3 (Phys 3): 3387 assigned | 3389 processed | 7 I stole | 5 stolen from me +Node 0 (Phys 0): 3397 assigned | 3397 processed | 4 I stole | 4 stolen from me +Node 1 (Phys 1): 3393 assigned | 3405 processed | 15 I stole | 3 stolen from me +Node 2 (Phys 2): 3382 assigned | 3376 processed | 0 I stole | 6 stolen from me +Node 3 (Phys 3): 3393 assigned | 3387 processed | 1 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 29 chunks (0.2%) +Total Cross-Socket Traffic: 20 chunks (0.1%) ================================================================= 0 -real 0m0.540s -user 0m4.063s -sys 0m3.451s +real 0m0.548s +user 0m4.042s +sys 0m3.554s -CPU UTILIZATION: 13.914 / 28 +CPU UTILIZATION: 13.861 / 28 ----------------------------------------- @@ -5000,11 +5000,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.828s -user 0m9.367s -sys 0m9.378s +real 0m0.826s +user 0m9.417s +sys 0m9.454s -CPU UTILIZATION: 22.638 / 28 +CPU UTILIZATION: 22.846 / 28 ----------------------------------------- @@ -5013,20 +5013,20 @@ CPU UTILIZATION: 22.638 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.889s -user 0m9.470s -sys 0m9.743s +real 0m0.900s +user 0m9.393s +sys 0m9.911s -CPU UTILIZATION: 21.611 / 28 +CPU UTILIZATION: 21.448 / 28 ----------------------------------------- @@ -5035,19 +5035,19 @@ CPU UTILIZATION: 21.611 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3421 assigned | 3413 processed | 108 I stole | 116 stolen from me -Node 1 (Phys 1): 3454 assigned | 3444 processed | 105 I stole | 115 stolen from me -Node 2 (Phys 2): 3311 assigned | 3320 processed | 113 I stole | 104 stolen from me -Node 3 (Phys 3): 3379 assigned | 3388 processed | 118 I stole | 109 stolen from me +Node 0 (Phys 0): 3409 assigned | 3394 processed | 101 I stole | 116 stolen from me +Node 1 (Phys 1): 3423 assigned | 3463 processed | 125 I stole | 85 stolen from me +Node 2 (Phys 2): 3319 assigned | 3298 processed | 99 I stole | 120 stolen from me +Node 3 (Phys 3): 3414 assigned | 3410 processed | 85 I stole | 89 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 444 chunks (3.3%) +Total Cross-Socket Traffic: 410 chunks (3.0%) ================================================================= -real 0m0.991s -user 0m12.103s -sys 0m10.834s +real 0m1.005s +user 0m12.093s +sys 0m11.032s -CPU UTILIZATION: 23.145 / 28 +CPU UTILIZATION: 23.009 / 28 ----------------------------------------- @@ -5056,20 +5056,20 @@ CPU UTILIZATION: 23.145 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3503 assigned | 3509 processed | 155 I stole | 149 stolen from me -Node 1 (Phys 1): 3387 assigned | 3360 processed | 133 I stole | 160 stolen from me -Node 2 (Phys 2): 3331 assigned | 3344 processed | 133 I stole | 120 stolen from me -Node 3 (Phys 3): 3344 assigned | 3352 processed | 140 I stole | 132 stolen from me +Node 0 (Phys 0): 3394 assigned | 3381 processed | 114 I stole | 127 stolen from me +Node 1 (Phys 1): 3409 assigned | 3411 processed | 121 I stole | 119 stolen from me +Node 2 (Phys 2): 3403 assigned | 3435 processed | 126 I stole | 94 stolen from me +Node 3 (Phys 3): 3359 assigned | 3338 processed | 93 I stole | 114 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 561 chunks (4.1%) +Total Cross-Socket Traffic: 454 chunks (3.3%) ================================================================= 100000000 -real 0m0.999s -user 0m12.175s -sys 0m11.152s +real 0m1.018s +user 0m12.203s +sys 0m11.424s -CPU UTILIZATION: 23.350 / 28 +CPU UTILIZATION: 23.209 / 28 ----------------------------------------- @@ -5079,18 +5079,18 @@ CPU UTILIZATION: 23.350 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.801s -user 0m9.354s -sys 0m8.984s +real 0m0.812s +user 0m9.489s +sys 0m8.993s -CPU UTILIZATION: 22.893 / 28 +CPU UTILIZATION: 22.761 / 28 ----------------------------------------- @@ -5099,20 +5099,20 @@ CPU UTILIZATION: 22.893 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 107 assigned | 107 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.885s -user 0m9.468s -sys 0m9.275s +real 0m0.888s +user 0m9.421s +sys 0m9.443s -CPU UTILIZATION: 21.178 / 28 +CPU UTILIZATION: 21.243 / 28 ----------------------------------------- @@ -5121,19 +5121,19 @@ CPU UTILIZATION: 21.178 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3397 assigned | 3392 processed | 97 I stole | 102 stolen from me -Node 1 (Phys 1): 3402 assigned | 3416 processed | 113 I stole | 99 stolen from me -Node 2 (Phys 2): 3379 assigned | 3368 processed | 108 I stole | 119 stolen from me -Node 3 (Phys 3): 3387 assigned | 3389 processed | 116 I stole | 114 stolen from me +Node 0 (Phys 0): 3425 assigned | 3422 processed | 84 I stole | 87 stolen from me +Node 1 (Phys 1): 3426 assigned | 3414 processed | 79 I stole | 91 stolen from me +Node 2 (Phys 2): 3351 assigned | 3345 processed | 81 I stole | 87 stolen from me +Node 3 (Phys 3): 3363 assigned | 3384 processed | 91 I stole | 70 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 434 chunks (3.2%) +Total Cross-Socket Traffic: 335 chunks (2.5%) ================================================================= -real 0m1.550s -user 0m12.131s -sys 0m10.929s +real 0m0.999s +user 0m12.130s +sys 0m10.549s -CPU UTILIZATION: 14.877 / 28 +CPU UTILIZATION: 22.701 / 28 ----------------------------------------- @@ -5142,20 +5142,20 @@ CPU UTILIZATION: 14.877 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3418 assigned | 3436 processed | 98 I stole | 80 stolen from me -Node 1 (Phys 1): 3446 assigned | 3440 processed | 83 I stole | 89 stolen from me -Node 2 (Phys 2): 3371 assigned | 3355 processed | 87 I stole | 103 stolen from me -Node 3 (Phys 3): 3330 assigned | 3334 processed | 87 I stole | 83 stolen from me +Node 0 (Phys 0): 3389 assigned | 3398 processed | 104 I stole | 95 stolen from me +Node 1 (Phys 1): 3395 assigned | 3401 processed | 94 I stole | 88 stolen from me +Node 2 (Phys 2): 3358 assigned | 3354 processed | 91 I stole | 95 stolen from me +Node 3 (Phys 3): 3423 assigned | 3412 processed | 78 I stole | 89 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 355 chunks (2.6%) +Total Cross-Socket Traffic: 367 chunks (2.7%) ================================================================= 100000000 -real 0m1.007s -user 0m12.224s -sys 0m10.776s +real 0m0.994s +user 0m12.115s +sys 0m10.905s -CPU UTILIZATION: 22.840 / 28 +CPU UTILIZATION: 23.158 / 28 ----------------------------------------- @@ -5165,18 +5165,18 @@ CPU UTILIZATION: 22.840 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (0.2%) ================================================================= -real 0m0.378s -user 0m0.175s -sys 0m0.689s +real 0m0.373s +user 0m0.161s +sys 0m0.681s -CPU UTILIZATION: 2.285 / 28 +CPU UTILIZATION: 2.257 / 28 ----------------------------------------- @@ -5185,20 +5185,20 @@ CPU UTILIZATION: 2.285 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 106 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 106 assigned | 107 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 106 assigned | 105 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (0.5%) ================================================================= 0 -real 0m0.377s -user 0m0.176s -sys 0m0.681s +real 0m0.380s +user 0m0.181s +sys 0m0.684s -CPU UTILIZATION: 2.273 / 28 +CPU UTILIZATION: 2.276 / 28 ----------------------------------------- @@ -5207,19 +5207,19 @@ CPU UTILIZATION: 2.273 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3401 assigned | 3410 processed | 11 I stole | 2 stolen from me -Node 1 (Phys 1): 3395 assigned | 3394 processed | 4 I stole | 5 stolen from me -Node 2 (Phys 2): 3387 assigned | 3382 processed | 2 I stole | 7 stolen from me -Node 3 (Phys 3): 3382 assigned | 3379 processed | 1 I stole | 4 stolen from me +Node 0 (Phys 0): 3390 assigned | 3404 processed | 14 I stole | 0 stolen from me +Node 1 (Phys 1): 3395 assigned | 3392 processed | 2 I stole | 5 stolen from me +Node 2 (Phys 2): 3388 assigned | 3383 processed | 1 I stole | 6 stolen from me +Node 3 (Phys 3): 3392 assigned | 3386 processed | 0 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 18 chunks (0.1%) +Total Cross-Socket Traffic: 17 chunks (0.1%) ================================================================= -real 0m0.463s -user 0m1.651s -sys 0m1.529s +real 0m0.487s +user 0m1.713s +sys 0m1.549s -CPU UTILIZATION: 6.868 / 28 +CPU UTILIZATION: 6.698 / 28 ----------------------------------------- @@ -5228,20 +5228,20 @@ CPU UTILIZATION: 6.868 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3401 assigned | 3413 processed | 12 I stole | 0 stolen from me -Node 1 (Phys 1): 3392 assigned | 3386 processed | 0 I stole | 6 stolen from me -Node 2 (Phys 2): 3388 assigned | 3385 processed | 1 I stole | 4 stolen from me -Node 3 (Phys 3): 3384 assigned | 3381 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 3396 assigned | 3407 processed | 11 I stole | 0 stolen from me +Node 1 (Phys 1): 3393 assigned | 3390 processed | 0 I stole | 3 stolen from me +Node 2 (Phys 2): 3388 assigned | 3384 processed | 0 I stole | 4 stolen from me +Node 3 (Phys 3): 3388 assigned | 3384 processed | 0 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 13 chunks (0.1%) +Total Cross-Socket Traffic: 11 chunks (0.1%) ================================================================= 0 -real 0m0.458s -user 0m1.706s -sys 0m1.494s +real 0m0.506s +user 0m1.750s +sys 0m1.572s -CPU UTILIZATION: 6.986 / 28 +CPU UTILIZATION: 6.565 / 28 ----------------------------------------- @@ -5258,11 +5258,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.393s -user 0m0.644s -sys 0m1.307s +real 0m0.401s +user 0m0.646s +sys 0m1.429s -CPU UTILIZATION: 4.964 / 28 +CPU UTILIZATION: 5.174 / 28 ----------------------------------------- @@ -5280,11 +5280,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.391s -user 0m0.675s -sys 0m1.586s +real 0m0.394s +user 0m0.658s +sys 0m1.633s -CPU UTILIZATION: 5.782 / 28 +CPU UTILIZATION: 5.814 / 28 ----------------------------------------- @@ -5293,19 +5293,19 @@ CPU UTILIZATION: 5.782 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3410 assigned | 3409 processed | 7 I stole | 8 stolen from me -Node 1 (Phys 1): 3385 assigned | 3387 processed | 7 I stole | 5 stolen from me -Node 2 (Phys 2): 3389 assigned | 3390 processed | 8 I stole | 7 stolen from me -Node 3 (Phys 3): 3381 assigned | 3379 processed | 2 I stole | 4 stolen from me +Node 0 (Phys 0): 3378 assigned | 3378 processed | 12 I stole | 12 stolen from me +Node 1 (Phys 1): 3408 assigned | 3406 processed | 11 I stole | 13 stolen from me +Node 2 (Phys 2): 3393 assigned | 3389 processed | 5 I stole | 9 stolen from me +Node 3 (Phys 3): 3386 assigned | 3392 processed | 10 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 24 chunks (0.2%) +Total Cross-Socket Traffic: 38 chunks (0.3%) ================================================================= -real 0m0.716s -user 0m4.727s -sys 0m4.332s +real 0m0.724s +user 0m4.736s +sys 0m4.377s -CPU UTILIZATION: 12.652 / 28 +CPU UTILIZATION: 12.587 / 28 ----------------------------------------- @@ -5314,20 +5314,20 @@ CPU UTILIZATION: 12.652 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3395 assigned | 3397 processed | 11 I stole | 9 stolen from me -Node 1 (Phys 1): 3398 assigned | 3393 processed | 6 I stole | 11 stolen from me -Node 2 (Phys 2): 3390 assigned | 3387 processed | 7 I stole | 10 stolen from me -Node 3 (Phys 3): 3382 assigned | 3388 processed | 10 I stole | 4 stolen from me +Node 0 (Phys 0): 3391 assigned | 3391 processed | 8 I stole | 8 stolen from me +Node 1 (Phys 1): 3402 assigned | 3402 processed | 8 I stole | 8 stolen from me +Node 2 (Phys 2): 3380 assigned | 3384 processed | 10 I stole | 6 stolen from me +Node 3 (Phys 3): 3392 assigned | 3388 processed | 4 I stole | 8 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 34 chunks (0.3%) +Total Cross-Socket Traffic: 30 chunks (0.2%) ================================================================= 100000000 -real 0m0.735s -user 0m4.845s -sys 0m4.647s +real 0m0.734s +user 0m4.837s +sys 0m4.740s -CPU UTILIZATION: 12.914 / 28 +CPU UTILIZATION: 13.047 / 28 ----------------------------------------- @@ -5344,11 +5344,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.377s -user 0m0.663s -sys 0m1.274s +real 0m0.388s +user 0m0.650s +sys 0m1.329s -CPU UTILIZATION: 5.137 / 28 +CPU UTILIZATION: 5.100 / 28 ----------------------------------------- @@ -5366,11 +5366,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m0.408s -user 0m0.696s -sys 0m1.657s +real 0m0.385s +user 0m0.666s +sys 0m1.593s -CPU UTILIZATION: 5.767 / 28 +CPU UTILIZATION: 5.867 / 28 ----------------------------------------- @@ -5379,19 +5379,19 @@ CPU UTILIZATION: 5.767 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3390 assigned | 3387 processed | 13 I stole | 16 stolen from me -Node 1 (Phys 1): 3395 assigned | 3396 processed | 11 I stole | 10 stolen from me -Node 2 (Phys 2): 3407 assigned | 3403 processed | 11 I stole | 15 stolen from me -Node 3 (Phys 3): 3373 assigned | 3379 processed | 10 I stole | 4 stolen from me +Node 0 (Phys 0): 3406 assigned | 3398 processed | 8 I stole | 16 stolen from me +Node 1 (Phys 1): 3381 assigned | 3386 processed | 13 I stole | 8 stolen from me +Node 2 (Phys 2): 3379 assigned | 3385 processed | 11 I stole | 5 stolen from me +Node 3 (Phys 3): 3399 assigned | 3396 processed | 7 I stole | 10 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 45 chunks (0.3%) +Total Cross-Socket Traffic: 39 chunks (0.3%) ================================================================= -real 0m0.695s -user 0m4.778s -sys 0m3.966s +real 0m0.699s +user 0m4.670s +sys 0m4.123s -CPU UTILIZATION: 12.581 / 28 +CPU UTILIZATION: 12.579 / 28 ----------------------------------------- @@ -5400,20 +5400,20 @@ CPU UTILIZATION: 12.581 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3396 assigned | 3394 processed | 11 I stole | 13 stolen from me -Node 1 (Phys 1): 3390 assigned | 3388 processed | 10 I stole | 12 stolen from me -Node 2 (Phys 2): 3392 assigned | 3394 processed | 11 I stole | 9 stolen from me -Node 3 (Phys 3): 3387 assigned | 3389 processed | 8 I stole | 6 stolen from me +Node 0 (Phys 0): 3384 assigned | 3384 processed | 12 I stole | 12 stolen from me +Node 1 (Phys 1): 3383 assigned | 3391 processed | 16 I stole | 8 stolen from me +Node 2 (Phys 2): 3399 assigned | 3391 processed | 4 I stole | 12 stolen from me +Node 3 (Phys 3): 3399 assigned | 3399 processed | 8 I stole | 8 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 40 chunks (0.3%) ================================================================= 100000000 -real 0m0.702s -user 0m4.829s -sys 0m4.361s +real 0m0.709s +user 0m4.779s +sys 0m4.523s -CPU UTILIZATION: 13.091 / 28 +CPU UTILIZATION: 13.119 / 28 ----------------------------------------- @@ -5422,19 +5422,19 @@ CPU UTILIZATION: 13.091 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 106 assigned | 106 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 105 assigned | 105 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 108 assigned | 108 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 110 assigned | 110 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 100 assigned | 100 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.805s -user 0m14.495s -sys 0m5.429s +real 0m0.815s +user 0m14.345s +sys 0m5.676s -CPU UTILIZATION: 24.750 / 28 +CPU UTILIZATION: 24.565 / 28 ----------------------------------------- @@ -5443,20 +5443,20 @@ CPU UTILIZATION: 24.750 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 107 assigned | 107 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 110 assigned | 110 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 109 assigned | 109 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 109 assigned | 109 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 105 assigned | 105 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 103 assigned | 103 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 102 assigned | 102 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.804s -user 0m14.358s -sys 0m5.568s +real 0m0.816s +user 0m14.562s +sys 0m5.593s -CPU UTILIZATION: 24.783 / 28 +CPU UTILIZATION: 24.699 / 28 ----------------------------------------- @@ -5465,19 +5465,19 @@ CPU UTILIZATION: 24.783 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3450 assigned | 3441 processed | 235 I stole | 244 stolen from me -Node 1 (Phys 1): 3400 assigned | 3417 processed | 239 I stole | 222 stolen from me -Node 2 (Phys 2): 3370 assigned | 3357 processed | 230 I stole | 243 stolen from me -Node 3 (Phys 3): 3345 assigned | 3350 processed | 222 I stole | 217 stolen from me +Node 0 (Phys 0): 3476 assigned | 3508 processed | 255 I stole | 223 stolen from me +Node 1 (Phys 1): 3383 assigned | 3406 processed | 218 I stole | 195 stolen from me +Node 2 (Phys 2): 3447 assigned | 3378 processed | 191 I stole | 260 stolen from me +Node 3 (Phys 3): 3259 assigned | 3273 processed | 208 I stole | 194 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 926 chunks (6.8%) +Total Cross-Socket Traffic: 872 chunks (6.4%) ================================================================= -real 0m1.044s -user 0m15.160s -sys 0m7.372s +real 0m1.041s +user 0m14.757s +sys 0m7.390s -CPU UTILIZATION: 21.582 / 28 +CPU UTILIZATION: 21.274 / 28 ----------------------------------------- @@ -5486,20 +5486,20 @@ CPU UTILIZATION: 21.582 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3481 assigned | 3420 processed | 231 I stole | 292 stolen from me -Node 1 (Phys 1): 3444 assigned | 3464 processed | 244 I stole | 224 stolen from me -Node 2 (Phys 2): 3318 assigned | 3340 processed | 258 I stole | 236 stolen from me -Node 3 (Phys 3): 3322 assigned | 3341 processed | 244 I stole | 225 stolen from me +Node 0 (Phys 0): 3419 assigned | 3417 processed | 264 I stole | 266 stolen from me +Node 1 (Phys 1): 3397 assigned | 3385 processed | 254 I stole | 266 stolen from me +Node 2 (Phys 2): 3403 assigned | 3409 processed | 246 I stole | 240 stolen from me +Node 3 (Phys 3): 3346 assigned | 3354 processed | 240 I stole | 232 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 977 chunks (7.2%) +Total Cross-Socket Traffic: 1004 chunks (7.4%) ================================================================= 0 -real 0m1.037s -user 0m15.011s -sys 0m7.497s +real 0m1.023s +user 0m14.750s +sys 0m7.325s -CPU UTILIZATION: 21.704 / 28 +CPU UTILIZATION: 21.578 / 28 ----------------------------------------- @@ -5516,11 +5516,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m5.684s -user 1m17.165s -sys 1m2.832s +real 0m5.732s +user 1m17.099s +sys 1m3.568s -CPU UTILIZATION: 24.630 / 28 +CPU UTILIZATION: 24.540 / 28 ----------------------------------------- @@ -5538,11 +5538,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m5.702s -user 1m17.206s -sys 1m3.186s +real 0m5.773s +user 1m17.161s +sys 1m4.848s -CPU UTILIZATION: 24.621 / 28 +CPU UTILIZATION: 24.598 / 28 ----------------------------------------- @@ -5551,19 +5551,19 @@ CPU UTILIZATION: 24.621 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3395 assigned | 3395 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 3391 assigned | 3391 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 3393 assigned | 3393 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3386 assigned | 3386 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 3398 assigned | 3400 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 3390 assigned | 3390 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 3394 assigned | 3393 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 3383 assigned | 3382 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.0%) ================================================================= -real 0m5.734s -user 1m17.361s -sys 1m3.855s +real 0m5.739s +user 1m17.037s +sys 1m4.356s -CPU UTILIZATION: 24.627 / 28 +CPU UTILIZATION: 24.637 / 28 ----------------------------------------- @@ -5572,20 +5572,20 @@ CPU UTILIZATION: 24.627 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3397 assigned | 3397 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 3385 assigned | 3385 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 3395 assigned | 3395 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 3388 assigned | 3388 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 3403 assigned | 3402 processed | 1 I stole | 2 stolen from me +Node 1 (Phys 1): 3393 assigned | 3392 processed | 2 I stole | 3 stolen from me +Node 2 (Phys 2): 3391 assigned | 3391 processed | 2 I stole | 2 stolen from me +Node 3 (Phys 3): 3378 assigned | 3380 processed | 3 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 8 chunks (0.1%) ================================================================= 100000000 -real 0m5.763s -user 1m17.218s -sys 1m4.951s +real 0m5.809s +user 1m17.489s +sys 1m5.803s -CPU UTILIZATION: 24.669 / 28 +CPU UTILIZATION: 24.667 / 28 ----------------------------------------- @@ -5602,11 +5602,11 @@ Node 3 (Phys 3): 106 assigned | 106 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m5.610s -user 1m16.980s -sys 1m1.029s +real 0m5.677s +user 1m16.787s +sys 1m2.697s -CPU UTILIZATION: 24.600 / 28 +CPU UTILIZATION: 24.570 / 28 ----------------------------------------- @@ -5624,11 +5624,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 100000000 -real 0m5.650s -user 1m16.983s -sys 1m1.990s +real 0m5.708s +user 1m17.309s +sys 1m3.034s -CPU UTILIZATION: 24.596 / 28 +CPU UTILIZATION: 24.587 / 28 ----------------------------------------- @@ -5637,19 +5637,19 @@ CPU UTILIZATION: 24.596 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3397 assigned | 3397 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 3394 assigned | 3395 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 3387 assigned | 3385 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 3387 assigned | 3388 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 3395 assigned | 3396 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 3401 assigned | 3402 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 3383 assigned | 3381 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 3386 assigned | 3386 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.0%) +Total Cross-Socket Traffic: 3 chunks (0.0%) ================================================================= -real 0m5.633s -user 1m17.105s -sys 1m1.563s +real 0m5.649s +user 1m16.588s +sys 1m2.467s -CPU UTILIZATION: 24.617 / 28 +CPU UTILIZATION: 24.615 / 28 ----------------------------------------- @@ -5658,20 +5658,20 @@ CPU UTILIZATION: 24.617 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 3402 assigned | 3402 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 3392 assigned | 3391 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 3393 assigned | 3394 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 3378 assigned | 3378 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 3398 assigned | 3397 processed | 2 I stole | 3 stolen from me +Node 1 (Phys 1): 3390 assigned | 3389 processed | 2 I stole | 3 stolen from me +Node 2 (Phys 2): 3392 assigned | 3393 processed | 2 I stole | 1 stolen from me +Node 3 (Phys 3): 3385 assigned | 3386 processed | 2 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.0%) +Total Cross-Socket Traffic: 8 chunks (0.1%) ================================================================= 100000000 -real 0m5.673s -user 1m17.320s -sys 1m2.579s +real 0m5.724s +user 1m17.252s +sys 1m3.823s -CPU UTILIZATION: 24.660 / 28 +CPU UTILIZATION: 24.646 / 28 ----------------------------------------- @@ -5680,19 +5680,19 @@ CPU UTILIZATION: 24.660 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.162s -user 0m0.585s -sys 0m1.152s +real 0m0.160s +user 0m0.603s +sys 0m1.168s -CPU UTILIZATION: 10.722 / 28 +CPU UTILIZATION: 11.068 / 28 ----------------------------------------- @@ -5701,20 +5701,20 @@ CPU UTILIZATION: 10.722 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 25 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 23 assigned | 22 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 18 assigned | 18 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 17 assigned | 17 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 25 assigned | 26 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 23 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 16 assigned | 15 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= 0 -real 0m0.158s -user 0m0.630s -sys 0m1.099s +real 0m0.164s +user 0m0.619s +sys 0m1.138s -CPU UTILIZATION: 10.943 / 28 +CPU UTILIZATION: 10.713 / 28 ----------------------------------------- @@ -5723,19 +5723,19 @@ CPU UTILIZATION: 10.943 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 647 assigned | 650 processed | 6 I stole | 3 stolen from me -Node 1 (Phys 1): 642 assigned | 642 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 637 assigned | 628 processed | 0 I stole | 9 stolen from me -Node 3 (Phys 3): 636 assigned | 642 processed | 8 I stole | 2 stolen from me +Node 0 (Phys 0): 644 assigned | 649 processed | 7 I stole | 2 stolen from me +Node 1 (Phys 1): 640 assigned | 640 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 635 assigned | 631 processed | 0 I stole | 4 stolen from me +Node 3 (Phys 3): 643 assigned | 642 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 16 chunks (0.6%) +Total Cross-Socket Traffic: 10 chunks (0.4%) ================================================================= -real 0m0.214s -user 0m1.527s -sys 0m1.619s +real 0m0.221s +user 0m1.514s +sys 0m1.675s -CPU UTILIZATION: 14.700 / 28 +CPU UTILIZATION: 14.429 / 28 ----------------------------------------- @@ -5744,20 +5744,20 @@ CPU UTILIZATION: 14.700 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 656 assigned | 658 processed | 3 I stole | 1 stolen from me -Node 1 (Phys 1): 633 assigned | 631 processed | 3 I stole | 5 stolen from me -Node 2 (Phys 2): 629 assigned | 626 processed | 3 I stole | 6 stolen from me -Node 3 (Phys 3): 644 assigned | 647 processed | 5 I stole | 2 stolen from me +Node 0 (Phys 0): 647 assigned | 650 processed | 4 I stole | 1 stolen from me +Node 1 (Phys 1): 651 assigned | 653 processed | 4 I stole | 2 stolen from me +Node 2 (Phys 2): 631 assigned | 627 processed | 0 I stole | 4 stolen from me +Node 3 (Phys 3): 633 assigned | 632 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 14 chunks (0.5%) +Total Cross-Socket Traffic: 9 chunks (0.4%) ================================================================= 0 -real 0m0.220s -user 0m1.522s -sys 0m1.640s +real 0m0.222s +user 0m1.524s +sys 0m1.621s -CPU UTILIZATION: 14.372 / 28 +CPU UTILIZATION: 14.166 / 28 ----------------------------------------- @@ -5766,19 +5766,19 @@ CPU UTILIZATION: 14.372 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= real 0m0.168s -user 0m0.670s -sys 0m1.326s +user 0m0.646s +sys 0m1.403s -CPU UTILIZATION: 11.880 / 28 +CPU UTILIZATION: 12.196 / 28 ----------------------------------------- @@ -5787,20 +5787,20 @@ CPU UTILIZATION: 11.880 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 1681 -real 0m0.185s -user 0m0.670s -sys 0m1.366s +real 0m0.195s +user 0m0.673s +sys 0m1.450s -CPU UTILIZATION: 11.005 / 28 +CPU UTILIZATION: 10.887 / 28 ----------------------------------------- @@ -5809,19 +5809,19 @@ CPU UTILIZATION: 11.005 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 651 assigned | 658 processed | 13 I stole | 6 stolen from me -Node 1 (Phys 1): 631 assigned | 629 processed | 8 I stole | 10 stolen from me -Node 2 (Phys 2): 639 assigned | 637 processed | 6 I stole | 8 stolen from me -Node 3 (Phys 3): 641 assigned | 638 processed | 7 I stole | 10 stolen from me +Node 0 (Phys 0): 654 assigned | 663 processed | 9 I stole | 0 stolen from me +Node 1 (Phys 1): 643 assigned | 645 processed | 5 I stole | 3 stolen from me +Node 2 (Phys 2): 638 assigned | 637 processed | 2 I stole | 3 stolen from me +Node 3 (Phys 3): 627 assigned | 617 processed | 0 I stole | 10 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 34 chunks (1.3%) +Total Cross-Socket Traffic: 16 chunks (0.6%) ================================================================= -real 0m0.230s -user 0m1.523s -sys 0m1.985s +real 0m0.232s +user 0m1.570s +sys 0m1.926s -CPU UTILIZATION: 15.252 / 28 +CPU UTILIZATION: 15.068 / 28 ----------------------------------------- @@ -5830,20 +5830,20 @@ CPU UTILIZATION: 15.252 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 632 assigned | 625 processed | 1 I stole | 8 stolen from me -Node 1 (Phys 1): 644 assigned | 646 processed | 7 I stole | 5 stolen from me -Node 2 (Phys 2): 625 assigned | 626 processed | 5 I stole | 4 stolen from me -Node 3 (Phys 3): 661 assigned | 665 processed | 8 I stole | 4 stolen from me +Node 0 (Phys 0): 652 assigned | 664 processed | 16 I stole | 4 stolen from me +Node 1 (Phys 1): 638 assigned | 638 processed | 6 I stole | 6 stolen from me +Node 2 (Phys 2): 633 assigned | 627 processed | 5 I stole | 11 stolen from me +Node 3 (Phys 3): 639 assigned | 633 processed | 5 I stole | 11 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 21 chunks (0.8%) +Total Cross-Socket Traffic: 32 chunks (1.2%) ================================================================= 3491 -real 0m0.232s -user 0m1.558s -sys 0m2.033s +real 0m0.236s +user 0m1.608s +sys 0m1.991s -CPU UTILIZATION: 15.478 / 28 +CPU UTILIZATION: 15.250 / 28 ----------------------------------------- @@ -5854,17 +5854,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.172s -user 0m1.061s -sys 0m1.411s +real 0m0.192s +user 0m1.117s +sys 0m1.442s -CPU UTILIZATION: 14.372 / 28 +CPU UTILIZATION: 13.328 / 28 ----------------------------------------- @@ -5873,20 +5873,20 @@ CPU UTILIZATION: 14.372 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 24 assigned | 25 processed | 1 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 2113621 -real 0m0.203s -user 0m1.041s -sys 0m1.555s +real 0m0.194s +user 0m1.109s +sys 0m1.442s -CPU UTILIZATION: 12.788 / 28 +CPU UTILIZATION: 13.149 / 28 ----------------------------------------- @@ -5895,19 +5895,19 @@ CPU UTILIZATION: 12.788 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 646 assigned | 652 processed | 17 I stole | 11 stolen from me -Node 1 (Phys 1): 633 assigned | 631 processed | 15 I stole | 17 stolen from me -Node 2 (Phys 2): 646 assigned | 638 processed | 11 I stole | 19 stolen from me -Node 3 (Phys 3): 637 assigned | 641 processed | 19 I stole | 15 stolen from me +Node 0 (Phys 0): 649 assigned | 649 processed | 21 I stole | 21 stolen from me +Node 1 (Phys 1): 636 assigned | 640 processed | 19 I stole | 15 stolen from me +Node 2 (Phys 2): 623 assigned | 619 processed | 14 I stole | 18 stolen from me +Node 3 (Phys 3): 654 assigned | 654 processed | 15 I stole | 15 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 62 chunks (2.4%) +Total Cross-Socket Traffic: 69 chunks (2.7%) ================================================================= -real 0m0.242s -user 0m1.732s -sys 0m2.192s +real 0m0.252s +user 0m1.711s +sys 0m2.221s -CPU UTILIZATION: 16.214 / 28 +CPU UTILIZATION: 15.603 / 28 ----------------------------------------- @@ -5916,20 +5916,20 @@ CPU UTILIZATION: 16.214 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 638 assigned | 643 processed | 15 I stole | 10 stolen from me -Node 1 (Phys 1): 648 assigned | 645 processed | 7 I stole | 10 stolen from me -Node 2 (Phys 2): 631 assigned | 632 processed | 13 I stole | 12 stolen from me -Node 3 (Phys 3): 645 assigned | 642 processed | 6 I stole | 9 stolen from me +Node 0 (Phys 0): 649 assigned | 644 processed | 11 I stole | 16 stolen from me +Node 1 (Phys 1): 644 assigned | 649 processed | 17 I stole | 12 stolen from me +Node 2 (Phys 2): 636 assigned | 645 processed | 20 I stole | 11 stolen from me +Node 3 (Phys 3): 633 assigned | 624 processed | 10 I stole | 19 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 41 chunks (1.6%) +Total Cross-Socket Traffic: 58 chunks (2.3%) ================================================================= 2113621 -real 0m0.246s -user 0m1.729s -sys 0m2.289s +real 0m0.244s +user 0m1.695s +sys 0m2.338s -CPU UTILIZATION: 16.333 / 28 +CPU UTILIZATION: 16.528 / 28 ----------------------------------------- @@ -5940,17 +5940,17 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.158s -user 0m0.537s -sys 0m1.073s +real 0m0.169s +user 0m0.557s +sys 0m1.117s -CPU UTILIZATION: 10.189 / 28 +CPU UTILIZATION: 9.905 / 28 ----------------------------------------- @@ -5959,20 +5959,20 @@ CPU UTILIZATION: 10.189 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 20 processed | 0 I stole | 2 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 19 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= 0 -real 0m0.160s -user 0m0.542s +real 0m0.161s +user 0m0.552s sys 0m1.115s -CPU UTILIZATION: 10.356 / 28 +CPU UTILIZATION: 10.354 / 28 ----------------------------------------- @@ -5981,19 +5981,19 @@ CPU UTILIZATION: 10.356 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 649 processed | 3 I stole | 3 stolen from me -Node 1 (Phys 1): 630 assigned | 628 processed | 1 I stole | 3 stolen from me -Node 2 (Phys 2): 648 assigned | 648 processed | 5 I stole | 5 stolen from me -Node 3 (Phys 3): 635 assigned | 637 processed | 4 I stole | 2 stolen from me +Node 0 (Phys 0): 645 assigned | 647 processed | 4 I stole | 2 stolen from me +Node 1 (Phys 1): 647 assigned | 648 processed | 4 I stole | 3 stolen from me +Node 2 (Phys 2): 643 assigned | 643 processed | 4 I stole | 4 stolen from me +Node 3 (Phys 3): 627 assigned | 624 processed | 1 I stole | 4 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 13 chunks (0.5%) ================================================================= -real 0m0.217s -user 0m1.497s -sys 0m1.611s +real 0m0.224s +user 0m1.455s +sys 0m1.679s -CPU UTILIZATION: 14.322 / 28 +CPU UTILIZATION: 13.991 / 28 ----------------------------------------- @@ -6002,20 +6002,20 @@ CPU UTILIZATION: 14.322 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 662 assigned | 664 processed | 5 I stole | 3 stolen from me -Node 1 (Phys 1): 644 assigned | 646 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 628 assigned | 628 processed | 2 I stole | 2 stolen from me -Node 3 (Phys 3): 628 assigned | 624 processed | 0 I stole | 4 stolen from me +Node 0 (Phys 0): 657 assigned | 659 processed | 8 I stole | 6 stolen from me +Node 1 (Phys 1): 647 assigned | 659 processed | 12 I stole | 0 stolen from me +Node 2 (Phys 2): 641 assigned | 638 processed | 3 I stole | 6 stolen from me +Node 3 (Phys 3): 617 assigned | 606 processed | 1 I stole | 12 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 11 chunks (0.4%) +Total Cross-Socket Traffic: 24 chunks (0.9%) ================================================================= 0 -real 0m0.216s -user 0m1.500s -sys 0m1.616s +real 0m0.220s +user 0m1.544s +sys 0m1.582s -CPU UTILIZATION: 14.425 / 28 +CPU UTILIZATION: 14.209 / 28 ----------------------------------------- @@ -6024,19 +6024,19 @@ CPU UTILIZATION: 14.425 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 24 assigned | 25 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 17 assigned | 17 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.165s -user 0m0.591s -sys 0m1.323s +real 0m0.167s +user 0m0.587s +sys 0m1.294s -CPU UTILIZATION: 11.600 / 28 +CPU UTILIZATION: 11.263 / 28 ----------------------------------------- @@ -6046,19 +6046,19 @@ CPU UTILIZATION: 11.600 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1479 -real 0m0.184s -user 0m0.626s -sys 0m1.359s +real 0m0.188s +user 0m0.645s +sys 0m1.328s -CPU UTILIZATION: 10.788 / 28 +CPU UTILIZATION: 10.494 / 28 ----------------------------------------- @@ -6067,19 +6067,19 @@ CPU UTILIZATION: 10.788 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 649 processed | 5 I stole | 5 stolen from me -Node 1 (Phys 1): 633 assigned | 641 processed | 11 I stole | 3 stolen from me -Node 2 (Phys 2): 638 assigned | 638 processed | 4 I stole | 4 stolen from me -Node 3 (Phys 3): 642 assigned | 634 processed | 1 I stole | 9 stolen from me +Node 0 (Phys 0): 644 assigned | 647 processed | 7 I stole | 4 stolen from me +Node 1 (Phys 1): 646 assigned | 646 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 641 assigned | 643 processed | 5 I stole | 3 stolen from me +Node 3 (Phys 3): 631 assigned | 626 processed | 2 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 21 chunks (0.8%) +Total Cross-Socket Traffic: 15 chunks (0.6%) ================================================================= -real 0m0.233s -user 0m1.561s -sys 0m1.934s +real 0m0.237s +user 0m1.556s +sys 0m1.917s -CPU UTILIZATION: 15.000 / 28 +CPU UTILIZATION: 14.654 / 28 ----------------------------------------- @@ -6088,20 +6088,20 @@ CPU UTILIZATION: 15.000 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 638 assigned | 642 processed | 9 I stole | 5 stolen from me -Node 1 (Phys 1): 644 assigned | 642 processed | 5 I stole | 7 stolen from me -Node 2 (Phys 2): 652 assigned | 647 processed | 4 I stole | 9 stolen from me -Node 3 (Phys 3): 628 assigned | 631 processed | 8 I stole | 5 stolen from me +Node 0 (Phys 0): 661 assigned | 661 processed | 7 I stole | 7 stolen from me +Node 1 (Phys 1): 625 assigned | 622 processed | 5 I stole | 8 stolen from me +Node 2 (Phys 2): 642 assigned | 647 processed | 10 I stole | 5 stolen from me +Node 3 (Phys 3): 634 assigned | 632 processed | 4 I stole | 6 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 26 chunks (1.0%) ================================================================= -3463 -real 0m0.234s -user 0m1.556s -sys 0m2.017s +3460 +real 0m0.237s +user 0m1.554s +sys 0m2.001s -CPU UTILIZATION: 15.269 / 28 +CPU UTILIZATION: 15.000 / 28 ----------------------------------------- @@ -6110,19 +6110,19 @@ CPU UTILIZATION: 15.269 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 24 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 17 processed | 0 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= -real 0m0.175s -user 0m0.976s -sys 0m1.350s +real 0m0.176s +user 0m0.985s +sys 0m1.331s -CPU UTILIZATION: 13.291 / 28 +CPU UTILIZATION: 13.159 / 28 ----------------------------------------- @@ -6133,18 +6133,18 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m0.186s -user 0m1.009s -sys 0m1.391s +real 0m0.199s +user 0m1.039s +sys 0m1.385s -CPU UTILIZATION: 12.903 / 28 +CPU UTILIZATION: 12.180 / 28 ----------------------------------------- @@ -6153,19 +6153,19 @@ CPU UTILIZATION: 12.903 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 652 assigned | 650 processed | 10 I stole | 12 stolen from me -Node 1 (Phys 1): 625 assigned | 619 processed | 7 I stole | 13 stolen from me -Node 2 (Phys 2): 639 assigned | 647 processed | 14 I stole | 6 stolen from me -Node 3 (Phys 3): 646 assigned | 646 processed | 9 I stole | 9 stolen from me +Node 0 (Phys 0): 643 assigned | 645 processed | 10 I stole | 8 stolen from me +Node 1 (Phys 1): 626 assigned | 618 processed | 7 I stole | 15 stolen from me +Node 2 (Phys 2): 665 assigned | 669 processed | 19 I stole | 15 stolen from me +Node 3 (Phys 3): 628 assigned | 630 processed | 13 I stole | 11 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 40 chunks (1.6%) +Total Cross-Socket Traffic: 49 chunks (1.9%) ================================================================= -real 0m0.241s -user 0m1.755s -sys 0m2.143s +real 0m0.251s +user 0m1.742s +sys 0m2.164s -CPU UTILIZATION: 16.174 / 28 +CPU UTILIZATION: 15.561 / 28 ----------------------------------------- @@ -6174,20 +6174,20 @@ CPU UTILIZATION: 16.174 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 650 processed | 12 I stole | 11 stolen from me -Node 1 (Phys 1): 626 assigned | 630 processed | 18 I stole | 14 stolen from me -Node 2 (Phys 2): 640 assigned | 639 processed | 10 I stole | 11 stolen from me -Node 3 (Phys 3): 647 assigned | 643 processed | 10 I stole | 14 stolen from me +Node 0 (Phys 0): 655 assigned | 659 processed | 14 I stole | 10 stolen from me +Node 1 (Phys 1): 653 assigned | 660 processed | 16 I stole | 9 stolen from me +Node 2 (Phys 2): 639 assigned | 639 processed | 12 I stole | 12 stolen from me +Node 3 (Phys 3): 615 assigned | 604 processed | 6 I stole | 17 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 50 chunks (2.0%) +Total Cross-Socket Traffic: 48 chunks (1.9%) ================================================================= 2113621 -real 0m0.243s -user 0m1.709s -sys 0m2.280s +real 0m0.247s +user 0m1.810s +sys 0m2.194s -CPU UTILIZATION: 16.415 / 28 +CPU UTILIZATION: 16.210 / 28 ----------------------------------------- @@ -6196,19 +6196,19 @@ CPU UTILIZATION: 16.415 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.159s -user 0m0.589s -sys 0m1.179s +real 0m0.163s +user 0m0.631s +sys 0m1.168s -CPU UTILIZATION: 11.119 / 28 +CPU UTILIZATION: 11.036 / 28 ----------------------------------------- @@ -6217,20 +6217,20 @@ CPU UTILIZATION: 11.119 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 real 0m0.162s -user 0m0.581s -sys 0m1.166s +user 0m0.632s +sys 0m1.148s -CPU UTILIZATION: 10.783 / 28 +CPU UTILIZATION: 10.987 / 28 ----------------------------------------- @@ -6239,19 +6239,19 @@ CPU UTILIZATION: 10.783 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 657 assigned | 661 processed | 5 I stole | 1 stolen from me -Node 1 (Phys 1): 646 assigned | 641 processed | 0 I stole | 5 stolen from me -Node 2 (Phys 2): 637 assigned | 640 processed | 3 I stole | 0 stolen from me -Node 3 (Phys 3): 622 assigned | 620 processed | 1 I stole | 3 stolen from me +Node 0 (Phys 0): 649 assigned | 652 processed | 5 I stole | 2 stolen from me +Node 1 (Phys 1): 655 assigned | 655 processed | 2 I stole | 2 stolen from me +Node 2 (Phys 2): 629 assigned | 627 processed | 3 I stole | 5 stolen from me +Node 3 (Phys 3): 629 assigned | 628 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.4%) +Total Cross-Socket Traffic: 11 chunks (0.4%) ================================================================= -real 0m0.221s -user 0m1.497s -sys 0m1.681s +real 0m0.220s +user 0m1.535s +sys 0m1.609s -CPU UTILIZATION: 14.380 / 28 +CPU UTILIZATION: 14.290 / 28 ----------------------------------------- @@ -6260,20 +6260,20 @@ CPU UTILIZATION: 14.380 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 657 assigned | 662 processed | 6 I stole | 1 stolen from me -Node 1 (Phys 1): 635 assigned | 631 processed | 1 I stole | 5 stolen from me -Node 2 (Phys 2): 640 assigned | 638 processed | 2 I stole | 4 stolen from me -Node 3 (Phys 3): 630 assigned | 631 processed | 3 I stole | 2 stolen from me +Node 0 (Phys 0): 657 assigned | 661 processed | 7 I stole | 3 stolen from me +Node 1 (Phys 1): 656 assigned | 655 processed | 4 I stole | 5 stolen from me +Node 2 (Phys 2): 629 assigned | 627 processed | 3 I stole | 5 stolen from me +Node 3 (Phys 3): 620 assigned | 619 processed | 3 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 12 chunks (0.5%) +Total Cross-Socket Traffic: 17 chunks (0.7%) ================================================================= 0 -real 0m0.216s -user 0m1.550s -sys 0m1.600s +real 0m0.221s +user 0m1.521s +sys 0m1.649s -CPU UTILIZATION: 14.583 / 28 +CPU UTILIZATION: 14.343 / 28 ----------------------------------------- @@ -6282,19 +6282,19 @@ CPU UTILIZATION: 14.583 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 19 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.161s -user 0m0.681s -sys 0m1.333s +real 0m0.169s +user 0m0.707s +sys 0m1.364s -CPU UTILIZATION: 12.509 / 28 +CPU UTILIZATION: 12.254 / 28 ----------------------------------------- @@ -6305,18 +6305,18 @@ NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.195s -user 0m0.694s -sys 0m1.410s +real 0m0.204s +user 0m0.665s +sys 0m1.475s -CPU UTILIZATION: 10.789 / 28 +CPU UTILIZATION: 10.490 / 28 ----------------------------------------- @@ -6325,19 +6325,19 @@ CPU UTILIZATION: 10.789 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 655 assigned | 665 processed | 14 I stole | 4 stolen from me -Node 1 (Phys 1): 634 assigned | 629 processed | 2 I stole | 7 stolen from me -Node 2 (Phys 2): 649 assigned | 649 processed | 4 I stole | 4 stolen from me -Node 3 (Phys 3): 624 assigned | 619 processed | 3 I stole | 8 stolen from me +Node 0 (Phys 0): 654 assigned | 658 processed | 5 I stole | 1 stolen from me +Node 1 (Phys 1): 641 assigned | 643 processed | 6 I stole | 4 stolen from me +Node 2 (Phys 2): 629 assigned | 621 processed | 3 I stole | 11 stolen from me +Node 3 (Phys 3): 638 assigned | 640 processed | 7 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 23 chunks (0.9%) +Total Cross-Socket Traffic: 21 chunks (0.8%) ================================================================= -real 0m0.228s -user 0m1.576s -sys 0m1.927s +real 0m0.241s +user 0m1.573s +sys 0m1.930s -CPU UTILIZATION: 15.364 / 28 +CPU UTILIZATION: 14.535 / 28 ----------------------------------------- @@ -6346,20 +6346,20 @@ CPU UTILIZATION: 15.364 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 667 assigned | 678 processed | 15 I stole | 4 stolen from me -Node 1 (Phys 1): 658 assigned | 649 processed | 0 I stole | 9 stolen from me -Node 2 (Phys 2): 609 assigned | 609 processed | 7 I stole | 7 stolen from me -Node 3 (Phys 3): 628 assigned | 626 processed | 9 I stole | 11 stolen from me +Node 0 (Phys 0): 667 assigned | 680 processed | 17 I stole | 4 stolen from me +Node 1 (Phys 1): 614 assigned | 604 processed | 2 I stole | 12 stolen from me +Node 2 (Phys 2): 646 assigned | 655 processed | 9 I stole | 0 stolen from me +Node 3 (Phys 3): 635 assigned | 623 processed | 2 I stole | 14 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 31 chunks (1.2%) +Total Cross-Socket Traffic: 30 chunks (1.2%) ================================================================= -3490 -real 0m0.232s -user 0m1.595s -sys 0m1.986s +3492 +real 0m0.237s +user 0m1.543s +sys 0m2.026s -CPU UTILIZATION: 15.435 / 28 +CPU UTILIZATION: 15.059 / 28 ----------------------------------------- @@ -6368,19 +6368,19 @@ CPU UTILIZATION: 15.435 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 22 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.172s -user 0m1.067s -sys 0m1.445s +real 0m0.178s +user 0m1.074s +sys 0m1.427s -CPU UTILIZATION: 14.604 / 28 +CPU UTILIZATION: 14.050 / 28 ----------------------------------------- @@ -6389,20 +6389,20 @@ CPU UTILIZATION: 14.604 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 19 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 2113621 -real 0m0.201s -user 0m1.048s -sys 0m1.459s +real 0m0.213s +user 0m1.119s +sys 0m1.489s -CPU UTILIZATION: 12.472 / 28 +CPU UTILIZATION: 12.244 / 28 ----------------------------------------- @@ -6411,19 +6411,19 @@ CPU UTILIZATION: 12.472 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 641 assigned | 636 processed | 14 I stole | 19 stolen from me -Node 1 (Phys 1): 653 assigned | 661 processed | 18 I stole | 10 stolen from me -Node 2 (Phys 2): 642 assigned | 646 processed | 15 I stole | 11 stolen from me -Node 3 (Phys 3): 626 assigned | 619 processed | 12 I stole | 19 stolen from me +Node 0 (Phys 0): 643 assigned | 648 processed | 12 I stole | 7 stolen from me +Node 1 (Phys 1): 658 assigned | 652 processed | 9 I stole | 15 stolen from me +Node 2 (Phys 2): 624 assigned | 620 processed | 8 I stole | 12 stolen from me +Node 3 (Phys 3): 637 assigned | 642 processed | 17 I stole | 12 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 59 chunks (2.3%) +Total Cross-Socket Traffic: 46 chunks (1.8%) ================================================================= -real 0m0.244s -user 0m1.715s -sys 0m2.173s +real 0m0.251s +user 0m1.745s +sys 0m2.154s -CPU UTILIZATION: 15.934 / 28 +CPU UTILIZATION: 15.533 / 28 ----------------------------------------- @@ -6432,20 +6432,20 @@ CPU UTILIZATION: 15.934 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 678 assigned | 687 processed | 19 I stole | 10 stolen from me -Node 1 (Phys 1): 645 assigned | 643 processed | 11 I stole | 13 stolen from me -Node 2 (Phys 2): 622 assigned | 621 processed | 12 I stole | 13 stolen from me -Node 3 (Phys 3): 617 assigned | 611 processed | 8 I stole | 14 stolen from me +Node 0 (Phys 0): 648 assigned | 649 processed | 10 I stole | 9 stolen from me +Node 1 (Phys 1): 644 assigned | 633 processed | 5 I stole | 16 stolen from me +Node 2 (Phys 2): 632 assigned | 639 processed | 15 I stole | 8 stolen from me +Node 3 (Phys 3): 638 assigned | 641 processed | 10 I stole | 7 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 50 chunks (2.0%) +Total Cross-Socket Traffic: 40 chunks (1.6%) ================================================================= 2113621 real 0m0.243s -user 0m1.714s -sys 0m2.243s +user 0m1.704s +sys 0m2.312s -CPU UTILIZATION: 16.283 / 28 +CPU UTILIZATION: 16.526 / 28 ----------------------------------------- @@ -6454,19 +6454,19 @@ CPU UTILIZATION: 16.283 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.161s -user 0m0.521s -sys 0m1.139s +real 0m0.159s +user 0m0.583s +sys 0m1.086s -CPU UTILIZATION: 10.310 / 28 +CPU UTILIZATION: 10.496 / 28 ----------------------------------------- @@ -6476,8 +6476,8 @@ CPU UTILIZATION: 10.310 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) @@ -6485,10 +6485,10 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) 0 real 0m0.164s -user 0m0.546s -sys 0m1.086s +user 0m0.557s +sys 0m1.111s -CPU UTILIZATION: 9.951 / 28 +CPU UTILIZATION: 10.170 / 28 ----------------------------------------- @@ -6497,19 +6497,19 @@ CPU UTILIZATION: 9.951 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 650 assigned | 659 processed | 12 I stole | 3 stolen from me -Node 1 (Phys 1): 641 assigned | 638 processed | 4 I stole | 7 stolen from me -Node 2 (Phys 2): 636 assigned | 639 processed | 8 I stole | 5 stolen from me -Node 3 (Phys 3): 635 assigned | 626 processed | 0 I stole | 9 stolen from me +Node 0 (Phys 0): 663 assigned | 665 processed | 4 I stole | 2 stolen from me +Node 1 (Phys 1): 642 assigned | 640 processed | 0 I stole | 2 stolen from me +Node 2 (Phys 2): 626 assigned | 627 processed | 2 I stole | 1 stolen from me +Node 3 (Phys 3): 631 assigned | 630 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 24 chunks (0.9%) +Total Cross-Socket Traffic: 6 chunks (0.2%) ================================================================= -real 0m0.217s -user 0m1.526s -sys 0m1.584s +real 0m0.220s +user 0m1.523s +sys 0m1.631s -CPU UTILIZATION: 14.331 / 28 +CPU UTILIZATION: 14.336 / 28 ----------------------------------------- @@ -6518,20 +6518,20 @@ CPU UTILIZATION: 14.331 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 657 assigned | 653 processed | 4 I stole | 8 stolen from me -Node 1 (Phys 1): 621 assigned | 617 processed | 4 I stole | 8 stolen from me -Node 2 (Phys 2): 639 assigned | 638 processed | 6 I stole | 7 stolen from me -Node 3 (Phys 3): 645 assigned | 654 processed | 13 I stole | 4 stolen from me +Node 0 (Phys 0): 647 assigned | 649 processed | 4 I stole | 2 stolen from me +Node 1 (Phys 1): 652 assigned | 649 processed | 1 I stole | 4 stolen from me +Node 2 (Phys 2): 632 assigned | 630 processed | 1 I stole | 3 stolen from me +Node 3 (Phys 3): 631 assigned | 634 processed | 5 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 27 chunks (1.1%) +Total Cross-Socket Traffic: 11 chunks (0.4%) ================================================================= 0 -real 0m0.217s -user 0m1.546s -sys 0m1.590s +real 0m0.221s +user 0m1.500s +sys 0m1.668s -CPU UTILIZATION: 14.451 / 28 +CPU UTILIZATION: 14.334 / 28 ----------------------------------------- @@ -6540,19 +6540,19 @@ CPU UTILIZATION: 14.451 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.163s -user 0m0.646s -sys 0m1.254s +real 0m0.166s +user 0m0.593s +sys 0m1.288s -CPU UTILIZATION: 11.656 / 28 +CPU UTILIZATION: 11.331 / 28 ----------------------------------------- @@ -6561,20 +6561,20 @@ CPU UTILIZATION: 11.656 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 17 assigned | 18 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 22 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -1476 -real 0m0.186s -user 0m0.633s -sys 0m1.293s +1479 +real 0m0.189s +user 0m0.615s +sys 0m1.385s -CPU UTILIZATION: 10.354 / 28 +CPU UTILIZATION: 10.582 / 28 ----------------------------------------- @@ -6583,19 +6583,19 @@ CPU UTILIZATION: 10.354 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 642 assigned | 649 processed | 11 I stole | 4 stolen from me -Node 1 (Phys 1): 654 assigned | 657 processed | 7 I stole | 4 stolen from me -Node 2 (Phys 2): 630 assigned | 620 processed | 3 I stole | 13 stolen from me -Node 3 (Phys 3): 636 assigned | 636 processed | 8 I stole | 8 stolen from me +Node 0 (Phys 0): 642 assigned | 644 processed | 5 I stole | 3 stolen from me +Node 1 (Phys 1): 626 assigned | 630 processed | 6 I stole | 2 stolen from me +Node 2 (Phys 2): 659 assigned | 662 processed | 5 I stole | 2 stolen from me +Node 3 (Phys 3): 635 assigned | 626 processed | 0 I stole | 9 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 29 chunks (1.1%) +Total Cross-Socket Traffic: 16 chunks (0.6%) ================================================================= -real 0m0.227s -user 0m1.569s -sys 0m1.903s +real 0m0.237s +user 0m1.549s +sys 0m1.924s -CPU UTILIZATION: 15.295 / 28 +CPU UTILIZATION: 14.654 / 28 ----------------------------------------- @@ -6604,20 +6604,20 @@ CPU UTILIZATION: 15.295 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 665 assigned | 671 processed | 15 I stole | 9 stolen from me -Node 1 (Phys 1): 650 assigned | 651 processed | 11 I stole | 10 stolen from me -Node 2 (Phys 2): 626 assigned | 624 processed | 7 I stole | 9 stolen from me -Node 3 (Phys 3): 621 assigned | 616 processed | 8 I stole | 13 stolen from me +Node 0 (Phys 0): 664 assigned | 671 processed | 10 I stole | 3 stolen from me +Node 1 (Phys 1): 664 assigned | 664 processed | 4 I stole | 4 stolen from me +Node 2 (Phys 2): 618 assigned | 613 processed | 0 I stole | 5 stolen from me +Node 3 (Phys 3): 616 assigned | 614 processed | 2 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 41 chunks (1.6%) +Total Cross-Socket Traffic: 16 chunks (0.6%) ================================================================= 3460 -real 0m0.231s -user 0m1.565s -sys 0m1.981s +real 0m0.234s +user 0m1.573s +sys 0m1.976s -CPU UTILIZATION: 15.350 / 28 +CPU UTILIZATION: 15.166 / 28 ----------------------------------------- @@ -6627,18 +6627,18 @@ CPU UTILIZATION: 15.350 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.177s -user 0m1.007s -sys 0m1.367s +real 0m0.179s +user 0m1.011s +sys 0m1.357s -CPU UTILIZATION: 13.412 / 28 +CPU UTILIZATION: 13.229 / 28 ----------------------------------------- @@ -6647,20 +6647,20 @@ CPU UTILIZATION: 13.412 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 22 processed | 0 I stole | 1 stolen from me +Node 1 (Phys 1): 21 assigned | 23 processed | 2 I stole | 0 stolen from me Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= 2113621 -real 0m0.197s -user 0m1.026s -sys 0m1.368s +real 0m0.203s +user 0m1.032s +sys 0m1.404s -CPU UTILIZATION: 12.152 / 28 +CPU UTILIZATION: 12.000 / 28 ----------------------------------------- @@ -6669,19 +6669,19 @@ CPU UTILIZATION: 12.152 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 632 assigned | 629 processed | 12 I stole | 15 stolen from me -Node 1 (Phys 1): 602 assigned | 598 processed | 7 I stole | 11 stolen from me -Node 2 (Phys 2): 663 assigned | 670 processed | 19 I stole | 12 stolen from me -Node 3 (Phys 3): 665 assigned | 665 processed | 12 I stole | 12 stolen from me +Node 0 (Phys 0): 674 assigned | 680 processed | 13 I stole | 7 stolen from me +Node 1 (Phys 1): 631 assigned | 636 processed | 16 I stole | 11 stolen from me +Node 2 (Phys 2): 640 assigned | 634 processed | 10 I stole | 16 stolen from me +Node 3 (Phys 3): 617 assigned | 612 processed | 7 I stole | 12 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 50 chunks (2.0%) +Total Cross-Socket Traffic: 46 chunks (1.8%) ================================================================= -real 0m0.242s -user 0m1.701s -sys 0m2.175s +real 0m0.251s +user 0m1.732s +sys 0m2.168s -CPU UTILIZATION: 16.016 / 28 +CPU UTILIZATION: 15.537 / 28 ----------------------------------------- @@ -6690,20 +6690,20 @@ CPU UTILIZATION: 16.016 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 656 assigned | 655 processed | 17 I stole | 18 stolen from me -Node 1 (Phys 1): 631 assigned | 625 processed | 14 I stole | 20 stolen from me -Node 2 (Phys 2): 625 assigned | 615 processed | 15 I stole | 25 stolen from me -Node 3 (Phys 3): 650 assigned | 667 processed | 32 I stole | 15 stolen from me +Node 0 (Phys 0): 641 assigned | 638 processed | 12 I stole | 15 stolen from me +Node 1 (Phys 1): 635 assigned | 636 processed | 17 I stole | 16 stolen from me +Node 2 (Phys 2): 642 assigned | 643 processed | 13 I stole | 12 stolen from me +Node 3 (Phys 3): 644 assigned | 645 processed | 15 I stole | 14 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 78 chunks (3.0%) +Total Cross-Socket Traffic: 57 chunks (2.2%) ================================================================= 2113621 -real 0m0.243s -user 0m1.789s -sys 0m2.187s +real 0m0.248s +user 0m1.724s +sys 0m2.262s -CPU UTILIZATION: 16.362 / 28 +CPU UTILIZATION: 16.072 / 28 ----------------------------------------- @@ -6712,19 +6712,19 @@ CPU UTILIZATION: 16.362 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= real 0m0.159s -user 0m0.568s -sys 0m1.150s +user 0m0.587s +sys 0m1.126s -CPU UTILIZATION: 10.805 / 28 +CPU UTILIZATION: 10.773 / 28 ----------------------------------------- @@ -6733,20 +6733,20 @@ CPU UTILIZATION: 10.805 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 17 assigned | 18 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= 0 -real 0m0.159s -user 0m0.563s -sys 0m1.134s +real 0m0.156s +user 0m0.560s +sys 0m1.131s -CPU UTILIZATION: 10.672 / 28 +CPU UTILIZATION: 10.839 / 28 ----------------------------------------- @@ -6755,19 +6755,19 @@ CPU UTILIZATION: 10.672 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 654 assigned | 651 processed | 2 I stole | 5 stolen from me -Node 1 (Phys 1): 632 assigned | 638 processed | 8 I stole | 2 stolen from me -Node 2 (Phys 2): 642 assigned | 643 processed | 3 I stole | 2 stolen from me -Node 3 (Phys 3): 634 assigned | 630 processed | 2 I stole | 6 stolen from me +Node 0 (Phys 0): 652 assigned | 659 processed | 7 I stole | 0 stolen from me +Node 1 (Phys 1): 644 assigned | 638 processed | 1 I stole | 7 stolen from me +Node 2 (Phys 2): 637 assigned | 638 processed | 4 I stole | 3 stolen from me +Node 3 (Phys 3): 629 assigned | 627 processed | 1 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 15 chunks (0.6%) +Total Cross-Socket Traffic: 13 chunks (0.5%) ================================================================= -real 0m0.217s -user 0m1.437s -sys 0m1.613s +real 0m0.220s +user 0m1.476s +sys 0m1.576s -CPU UTILIZATION: 14.055 / 28 +CPU UTILIZATION: 13.872 / 28 ----------------------------------------- @@ -6776,20 +6776,20 @@ CPU UTILIZATION: 14.055 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 665 assigned | 678 processed | 13 I stole | 0 stolen from me -Node 1 (Phys 1): 632 assigned | 630 processed | 3 I stole | 5 stolen from me -Node 2 (Phys 2): 641 assigned | 638 processed | 2 I stole | 5 stolen from me -Node 3 (Phys 3): 624 assigned | 616 processed | 2 I stole | 10 stolen from me +Node 0 (Phys 0): 652 assigned | 652 processed | 2 I stole | 2 stolen from me +Node 1 (Phys 1): 638 assigned | 633 processed | 1 I stole | 6 stolen from me +Node 2 (Phys 2): 659 assigned | 664 processed | 6 I stole | 1 stolen from me +Node 3 (Phys 3): 613 assigned | 613 processed | 2 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 20 chunks (0.8%) +Total Cross-Socket Traffic: 11 chunks (0.4%) ================================================================= 0 -real 0m0.221s -user 0m1.421s -sys 0m1.591s +real 0m0.225s +user 0m1.515s +sys 0m1.547s -CPU UTILIZATION: 13.628 / 28 +CPU UTILIZATION: 13.608 / 28 ----------------------------------------- @@ -6798,19 +6798,19 @@ CPU UTILIZATION: 13.628 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 18 assigned | 19 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 20 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= -real 0m0.162s -user 0m0.617s -sys 0m1.198s +real 0m0.163s +user 0m0.593s +sys 0m1.238s -CPU UTILIZATION: 11.203 / 28 +CPU UTILIZATION: 11.233 / 28 ----------------------------------------- @@ -6819,20 +6819,20 @@ CPU UTILIZATION: 11.203 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.175s -user 0m0.649s -sys 0m1.791s +real 0m0.179s +user 0m0.628s +sys 0m1.907s -CPU UTILIZATION: 13.942 / 28 +CPU UTILIZATION: 14.162 / 28 ----------------------------------------- @@ -6841,19 +6841,19 @@ CPU UTILIZATION: 13.942 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 657 assigned | 668 processed | 13 I stole | 2 stolen from me -Node 1 (Phys 1): 641 assigned | 640 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 634 assigned | 630 processed | 1 I stole | 5 stolen from me -Node 3 (Phys 3): 630 assigned | 624 processed | 2 I stole | 8 stolen from me +Node 0 (Phys 0): 621 assigned | 616 processed | 1 I stole | 6 stolen from me +Node 1 (Phys 1): 648 assigned | 653 processed | 7 I stole | 2 stolen from me +Node 2 (Phys 2): 642 assigned | 640 processed | 2 I stole | 4 stolen from me +Node 3 (Phys 3): 651 assigned | 653 processed | 4 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 18 chunks (0.7%) +Total Cross-Socket Traffic: 14 chunks (0.5%) ================================================================= -real 0m0.220s -user 0m1.486s -sys 0m1.749s +real 0m0.228s +user 0m1.570s +sys 0m1.665s -CPU UTILIZATION: 14.704 / 28 +CPU UTILIZATION: 14.188 / 28 ----------------------------------------- @@ -6862,20 +6862,20 @@ CPU UTILIZATION: 14.704 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 660 assigned | 663 processed | 9 I stole | 6 stolen from me -Node 1 (Phys 1): 652 assigned | 654 processed | 7 I stole | 5 stolen from me -Node 2 (Phys 2): 636 assigned | 630 processed | 7 I stole | 13 stolen from me -Node 3 (Phys 3): 614 assigned | 615 processed | 8 I stole | 7 stolen from me +Node 0 (Phys 0): 631 assigned | 635 processed | 8 I stole | 4 stolen from me +Node 1 (Phys 1): 655 assigned | 654 processed | 5 I stole | 6 stolen from me +Node 2 (Phys 2): 652 assigned | 649 processed | 4 I stole | 7 stolen from me +Node 3 (Phys 3): 624 assigned | 624 processed | 6 I stole | 6 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 31 chunks (1.2%) +Total Cross-Socket Traffic: 23 chunks (0.9%) ================================================================= -3496 -real 0m0.227s -user 0m1.490s -sys 0m1.894s +3494 +real 0m0.232s +user 0m1.520s +sys 0m1.937s -CPU UTILIZATION: 14.907 / 28 +CPU UTILIZATION: 14.900 / 28 ----------------------------------------- @@ -6884,19 +6884,19 @@ CPU UTILIZATION: 14.907 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 21 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 20 assigned | 21 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 21 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.168s -user 0m0.984s -sys 0m1.320s +real 0m0.173s +user 0m1.002s +sys 0m1.304s -CPU UTILIZATION: 13.714 / 28 +CPU UTILIZATION: 13.329 / 28 ----------------------------------------- @@ -6906,19 +6906,19 @@ CPU UTILIZATION: 13.714 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 21 assigned | 21 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m0.186s -user 0m0.984s -sys 0m1.672s +real 0m0.188s +user 0m1.079s +sys 0m1.701s -CPU UTILIZATION: 14.279 / 28 +CPU UTILIZATION: 14.787 / 28 ----------------------------------------- @@ -6927,17 +6927,17 @@ CPU UTILIZATION: 14.279 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 650 assigned | 651 processed | 15 I stole | 14 stolen from me -Node 1 (Phys 1): 653 assigned | 647 processed | 8 I stole | 14 stolen from me -Node 2 (Phys 2): 632 assigned | 630 processed | 6 I stole | 8 stolen from me -Node 3 (Phys 3): 627 assigned | 634 processed | 11 I stole | 4 stolen from me +Node 0 (Phys 0): 654 assigned | 662 processed | 14 I stole | 6 stolen from me +Node 1 (Phys 1): 626 assigned | 616 processed | 2 I stole | 12 stolen from me +Node 2 (Phys 2): 627 assigned | 626 processed | 8 I stole | 9 stolen from me +Node 3 (Phys 3): 655 assigned | 658 processed | 13 I stole | 10 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 40 chunks (1.6%) +Total Cross-Socket Traffic: 37 chunks (1.4%) ================================================================= real 0m0.232s -user 0m1.703s -sys 0m1.963s +user 0m1.645s +sys 0m2.021s CPU UTILIZATION: 15.801 / 28 @@ -6948,20 +6948,20 @@ CPU UTILIZATION: 15.801 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 654 assigned | 653 processed | 16 I stole | 17 stolen from me -Node 1 (Phys 1): 651 assigned | 662 processed | 24 I stole | 13 stolen from me -Node 2 (Phys 2): 625 assigned | 620 processed | 12 I stole | 17 stolen from me -Node 3 (Phys 3): 632 assigned | 627 processed | 13 I stole | 18 stolen from me +Node 0 (Phys 0): 646 assigned | 650 processed | 15 I stole | 11 stolen from me +Node 1 (Phys 1): 652 assigned | 660 processed | 16 I stole | 8 stolen from me +Node 2 (Phys 2): 627 assigned | 628 processed | 14 I stole | 13 stolen from me +Node 3 (Phys 3): 637 assigned | 624 processed | 8 I stole | 21 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 65 chunks (2.5%) +Total Cross-Socket Traffic: 53 chunks (2.1%) ================================================================= 2113621 -real 0m0.232s -user 0m1.742s -sys 0m2.054s +real 0m0.242s +user 0m1.770s +sys 0m2.068s -CPU UTILIZATION: 16.362 / 28 +CPU UTILIZATION: 15.859 / 28 ----------------------------------------- @@ -6970,19 +6970,19 @@ CPU UTILIZATION: 16.362 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 21 processed | 0 I stole | 1 stolen from me Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.156s -user 0m0.532s -sys 0m1.049s +real 0m0.159s +user 0m0.520s +sys 0m1.065s -CPU UTILIZATION: 10.134 / 28 +CPU UTILIZATION: 9.968 / 28 ----------------------------------------- @@ -6992,19 +6992,19 @@ CPU UTILIZATION: 10.134 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 17 assigned | 17 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 real 0m0.164s -user 0m0.493s -sys 0m1.078s +user 0m0.532s +sys 0m1.101s -CPU UTILIZATION: 9.579 / 28 +CPU UTILIZATION: 9.957 / 28 ----------------------------------------- @@ -7013,19 +7013,19 @@ CPU UTILIZATION: 9.579 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 636 assigned | 639 processed | 5 I stole | 2 stolen from me -Node 1 (Phys 1): 645 assigned | 650 processed | 6 I stole | 1 stolen from me -Node 2 (Phys 2): 644 assigned | 639 processed | 2 I stole | 7 stolen from me -Node 3 (Phys 3): 637 assigned | 634 processed | 1 I stole | 4 stolen from me +Node 0 (Phys 0): 639 assigned | 640 processed | 3 I stole | 2 stolen from me +Node 1 (Phys 1): 646 assigned | 648 processed | 4 I stole | 2 stolen from me +Node 2 (Phys 2): 652 assigned | 650 processed | 2 I stole | 4 stolen from me +Node 3 (Phys 3): 625 assigned | 624 processed | 2 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 14 chunks (0.5%) +Total Cross-Socket Traffic: 11 chunks (0.4%) ================================================================= -real 0m0.212s -user 0m1.504s -sys 0m1.514s +real 0m0.217s +user 0m1.446s +sys 0m1.591s -CPU UTILIZATION: 14.235 / 28 +CPU UTILIZATION: 13.995 / 28 ----------------------------------------- @@ -7034,20 +7034,20 @@ CPU UTILIZATION: 14.235 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 657 processed | 9 I stole | 1 stolen from me -Node 1 (Phys 1): 629 assigned | 625 processed | 1 I stole | 5 stolen from me -Node 2 (Phys 2): 648 assigned | 649 processed | 5 I stole | 4 stolen from me -Node 3 (Phys 3): 636 assigned | 631 processed | 2 I stole | 7 stolen from me +Node 0 (Phys 0): 647 assigned | 654 processed | 7 I stole | 0 stolen from me +Node 1 (Phys 1): 648 assigned | 644 processed | 0 I stole | 4 stolen from me +Node 2 (Phys 2): 633 assigned | 632 processed | 1 I stole | 2 stolen from me +Node 3 (Phys 3): 634 assigned | 632 processed | 2 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 17 chunks (0.7%) +Total Cross-Socket Traffic: 10 chunks (0.4%) ================================================================= 0 -real 0m0.211s -user 0m1.471s -sys 0m1.565s +real 0m0.219s +user 0m1.451s +sys 0m1.598s -CPU UTILIZATION: 14.388 / 28 +CPU UTILIZATION: 13.922 / 28 ----------------------------------------- @@ -7056,19 +7056,19 @@ CPU UTILIZATION: 14.388 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 24 assigned | 24 processed | 1 I stole | 1 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 2 chunks (2.4%) ================================================================= -real 0m0.164s -user 0m0.586s -sys 0m1.100s +real 0m0.161s +user 0m0.574s +sys 0m1.166s -CPU UTILIZATION: 10.280 / 28 +CPU UTILIZATION: 10.807 / 28 ----------------------------------------- @@ -7076,21 +7076,21 @@ CPU UTILIZATION: 10.280 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) -================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +================================================================= +Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -1479 -real 0m0.182s -user 0m0.596s -sys 0m1.825s +1476 +real 0m0.181s +user 0m0.605s +sys 0m1.854s -CPU UTILIZATION: 13.302 / 28 +CPU UTILIZATION: 13.585 / 28 ----------------------------------------- @@ -7099,19 +7099,19 @@ CPU UTILIZATION: 13.302 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 656 assigned | 659 processed | 5 I stole | 2 stolen from me -Node 1 (Phys 1): 660 assigned | 658 processed | 3 I stole | 5 stolen from me -Node 2 (Phys 2): 624 assigned | 628 processed | 6 I stole | 2 stolen from me -Node 3 (Phys 3): 622 assigned | 617 processed | 0 I stole | 5 stolen from me +Node 0 (Phys 0): 666 assigned | 666 processed | 4 I stole | 4 stolen from me +Node 1 (Phys 1): 639 assigned | 635 processed | 3 I stole | 7 stolen from me +Node 2 (Phys 2): 630 assigned | 631 processed | 4 I stole | 3 stolen from me +Node 3 (Phys 3): 627 assigned | 630 processed | 7 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 14 chunks (0.5%) +Total Cross-Socket Traffic: 18 chunks (0.7%) ================================================================= -real 0m0.218s -user 0m1.510s -sys 0m1.713s +real 0m0.221s +user 0m1.525s +sys 0m1.692s -CPU UTILIZATION: 14.784 / 28 +CPU UTILIZATION: 14.556 / 28 ----------------------------------------- @@ -7120,20 +7120,20 @@ CPU UTILIZATION: 14.784 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 646 assigned | 647 processed | 7 I stole | 6 stolen from me -Node 1 (Phys 1): 656 assigned | 660 processed | 11 I stole | 7 stolen from me -Node 2 (Phys 2): 637 assigned | 636 processed | 4 I stole | 5 stolen from me -Node 3 (Phys 3): 623 assigned | 619 processed | 3 I stole | 7 stolen from me +Node 0 (Phys 0): 639 assigned | 649 processed | 13 I stole | 3 stolen from me +Node 1 (Phys 1): 661 assigned | 657 processed | 4 I stole | 8 stolen from me +Node 2 (Phys 2): 645 assigned | 645 processed | 5 I stole | 5 stolen from me +Node 3 (Phys 3): 617 assigned | 611 processed | 3 I stole | 9 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 25 chunks (1.0%) ================================================================= 3459 -real 0m0.223s -user 0m1.469s -sys 0m1.916s +real 0m0.230s +user 0m1.447s +sys 0m1.981s -CPU UTILIZATION: 15.179 / 28 +CPU UTILIZATION: 14.904 / 28 ----------------------------------------- @@ -7142,19 +7142,19 @@ CPU UTILIZATION: 15.179 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 24 assigned | 24 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 17 assigned | 17 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.169s -user 0m0.963s -sys 0m1.164s +real 0m0.170s +user 0m0.994s +sys 0m1.184s -CPU UTILIZATION: 12.585 / 28 +CPU UTILIZATION: 12.811 / 28 ----------------------------------------- @@ -7163,20 +7163,20 @@ CPU UTILIZATION: 12.585 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 19 assigned | 20 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m0.182s -user 0m0.988s -sys 0m1.590s +real 0m0.187s +user 0m0.961s +sys 0m1.618s -CPU UTILIZATION: 14.164 / 28 +CPU UTILIZATION: 13.791 / 28 ----------------------------------------- @@ -7185,19 +7185,19 @@ CPU UTILIZATION: 14.164 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 650 assigned | 655 processed | 13 I stole | 8 stolen from me -Node 1 (Phys 1): 679 assigned | 683 processed | 12 I stole | 8 stolen from me -Node 2 (Phys 2): 617 assigned | 613 processed | 7 I stole | 11 stolen from me -Node 3 (Phys 3): 616 assigned | 611 processed | 7 I stole | 12 stolen from me +Node 0 (Phys 0): 649 assigned | 658 processed | 14 I stole | 5 stolen from me +Node 1 (Phys 1): 657 assigned | 656 processed | 10 I stole | 11 stolen from me +Node 2 (Phys 2): 643 assigned | 649 processed | 7 I stole | 1 stolen from me +Node 3 (Phys 3): 613 assigned | 599 processed | 0 I stole | 14 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 39 chunks (1.5%) +Total Cross-Socket Traffic: 31 chunks (1.2%) ================================================================= -real 0m0.225s -user 0m1.595s -sys 0m1.978s +real 0m0.234s +user 0m1.733s +sys 0m1.903s -CPU UTILIZATION: 15.880 / 28 +CPU UTILIZATION: 15.538 / 28 ----------------------------------------- @@ -7206,20 +7206,20 @@ CPU UTILIZATION: 15.880 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 652 assigned | 648 processed | 14 I stole | 18 stolen from me -Node 1 (Phys 1): 652 assigned | 659 processed | 15 I stole | 8 stolen from me -Node 2 (Phys 2): 625 assigned | 620 processed | 11 I stole | 16 stolen from me -Node 3 (Phys 3): 633 assigned | 635 processed | 13 I stole | 11 stolen from me +Node 0 (Phys 0): 672 assigned | 678 processed | 14 I stole | 8 stolen from me +Node 1 (Phys 1): 639 assigned | 637 processed | 7 I stole | 9 stolen from me +Node 2 (Phys 2): 642 assigned | 641 processed | 12 I stole | 13 stolen from me +Node 3 (Phys 3): 609 assigned | 606 processed | 8 I stole | 11 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 53 chunks (2.1%) +Total Cross-Socket Traffic: 41 chunks (1.6%) ================================================================= 2113621 -real 0m0.234s -user 0m1.761s -sys 0m2.028s +real 0m0.237s +user 0m1.742s +sys 0m2.047s -CPU UTILIZATION: 16.192 / 28 +CPU UTILIZATION: 15.987 / 28 ----------------------------------------- @@ -7229,18 +7229,18 @@ CPU UTILIZATION: 16.192 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.357s -user 0m7.101s -sys 0m0.393s +real 0m0.370s +user 0m7.105s +sys 0m0.401s -CPU UTILIZATION: 20.991 / 28 +CPU UTILIZATION: 20.286 / 28 ----------------------------------------- @@ -7249,8 +7249,8 @@ CPU UTILIZATION: 20.991 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- @@ -7258,11 +7258,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.357s -user 0m7.093s +real 0m0.365s +user 0m7.190s sys 0m0.409s -CPU UTILIZATION: 21.014 / 28 +CPU UTILIZATION: 20.819 / 28 ----------------------------------------- @@ -7271,19 +7271,19 @@ CPU UTILIZATION: 21.014 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 660 assigned | 680 processed | 94 I stole | 74 stolen from me -Node 1 (Phys 1): 604 assigned | 613 processed | 79 I stole | 70 stolen from me -Node 2 (Phys 2): 653 assigned | 627 processed | 66 I stole | 92 stolen from me -Node 3 (Phys 3): 645 assigned | 642 processed | 72 I stole | 75 stolen from me +Node 0 (Phys 0): 649 assigned | 667 processed | 97 I stole | 79 stolen from me +Node 1 (Phys 1): 627 assigned | 628 processed | 87 I stole | 86 stolen from me +Node 2 (Phys 2): 647 assigned | 616 processed | 69 I stole | 100 stolen from me +Node 3 (Phys 3): 639 assigned | 651 processed | 95 I stole | 83 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 311 chunks (12.1%) +Total Cross-Socket Traffic: 348 chunks (13.6%) ================================================================= real 0m0.351s -user 0m7.036s -sys 0m0.380s +user 0m6.879s +sys 0m0.407s -CPU UTILIZATION: 21.128 / 28 +CPU UTILIZATION: 20.757 / 28 ----------------------------------------- @@ -7292,20 +7292,20 @@ CPU UTILIZATION: 21.128 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 641 assigned | 643 processed | 71 I stole | 69 stolen from me -Node 1 (Phys 1): 625 assigned | 645 processed | 75 I stole | 55 stolen from me -Node 2 (Phys 2): 636 assigned | 598 processed | 52 I stole | 90 stolen from me -Node 3 (Phys 3): 660 assigned | 676 processed | 71 I stole | 55 stolen from me +Node 0 (Phys 0): 623 assigned | 648 processed | 112 I stole | 87 stolen from me +Node 1 (Phys 1): 659 assigned | 645 processed | 75 I stole | 89 stolen from me +Node 2 (Phys 2): 639 assigned | 639 processed | 75 I stole | 75 stolen from me +Node 3 (Phys 3): 641 assigned | 630 processed | 70 I stole | 81 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 269 chunks (10.5%) +Total Cross-Socket Traffic: 332 chunks (13.0%) ================================================================= 0 -real 0m0.350s -user 0m6.883s -sys 0m0.419s +real 0m0.356s +user 0m6.958s +sys 0m0.414s -CPU UTILIZATION: 20.862 / 28 +CPU UTILIZATION: 20.707 / 28 ----------------------------------------- @@ -7314,19 +7314,19 @@ CPU UTILIZATION: 20.862 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.382s -user 0m7.583s -sys 0m0.531s +real 0m0.379s +user 0m7.594s +sys 0m0.538s -CPU UTILIZATION: 21.240 / 28 +CPU UTILIZATION: 21.456 / 28 ----------------------------------------- @@ -7335,20 +7335,20 @@ CPU UTILIZATION: 21.240 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 1681 -real 0m0.383s -user 0m7.521s -sys 0m0.569s +real 0m0.379s +user 0m7.538s +sys 0m0.595s -CPU UTILIZATION: 21.122 / 28 +CPU UTILIZATION: 21.459 / 28 ----------------------------------------- @@ -7357,19 +7357,19 @@ CPU UTILIZATION: 21.122 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 658 assigned | 650 processed | 97 I stole | 105 stolen from me -Node 1 (Phys 1): 659 assigned | 648 processed | 84 I stole | 95 stolen from me -Node 2 (Phys 2): 641 assigned | 638 processed | 76 I stole | 79 stolen from me -Node 3 (Phys 3): 604 assigned | 626 processed | 108 I stole | 86 stolen from me +Node 0 (Phys 0): 642 assigned | 635 processed | 55 I stole | 62 stolen from me +Node 1 (Phys 1): 659 assigned | 661 processed | 61 I stole | 59 stolen from me +Node 2 (Phys 2): 655 assigned | 634 processed | 28 I stole | 49 stolen from me +Node 3 (Phys 3): 606 assigned | 632 processed | 69 I stole | 43 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 365 chunks (14.2%) +Total Cross-Socket Traffic: 213 chunks (8.3%) ================================================================= -real 0m0.369s -user 0m7.422s -sys 0m0.563s +real 0m0.366s +user 0m7.390s +sys 0m0.552s -CPU UTILIZATION: 21.639 / 28 +CPU UTILIZATION: 21.699 / 28 ----------------------------------------- @@ -7378,20 +7378,20 @@ CPU UTILIZATION: 21.639 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 666 assigned | 659 processed | 86 I stole | 93 stolen from me -Node 1 (Phys 1): 657 assigned | 671 processed | 105 I stole | 91 stolen from me -Node 2 (Phys 2): 625 assigned | 648 processed | 115 I stole | 92 stolen from me -Node 3 (Phys 3): 614 assigned | 584 processed | 67 I stole | 97 stolen from me +Node 0 (Phys 0): 642 assigned | 601 processed | 88 I stole | 129 stolen from me +Node 1 (Phys 1): 662 assigned | 664 processed | 109 I stole | 107 stolen from me +Node 2 (Phys 2): 635 assigned | 652 processed | 96 I stole | 79 stolen from me +Node 3 (Phys 3): 623 assigned | 645 processed | 104 I stole | 82 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 373 chunks (14.6%) +Total Cross-Socket Traffic: 397 chunks (15.5%) ================================================================= -3491 -real 0m0.375s -user 0m7.194s -sys 0m0.593s +3488 +real 0m0.381s +user 0m7.262s +sys 0m0.612s -CPU UTILIZATION: 20.765 / 28 +CPU UTILIZATION: 20.666 / 28 ----------------------------------------- @@ -7400,19 +7400,19 @@ CPU UTILIZATION: 20.765 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.468s -user 0m8.553s -sys 0m1.582s +real 0m0.459s +user 0m8.560s +sys 0m1.542s -CPU UTILIZATION: 21.655 / 28 +CPU UTILIZATION: 22.008 / 28 ----------------------------------------- @@ -7421,20 +7421,20 @@ CPU UTILIZATION: 21.655 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2168851 -real 0m0.465s -user 0m8.523s -sys 0m1.660s +real 0m0.468s +user 0m8.462s +sys 0m1.656s -CPU UTILIZATION: 21.898 / 28 +CPU UTILIZATION: 21.619 / 28 ----------------------------------------- @@ -7443,19 +7443,19 @@ CPU UTILIZATION: 21.898 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 654 assigned | 647 processed | 32 I stole | 39 stolen from me -Node 1 (Phys 1): 632 assigned | 613 processed | 29 I stole | 48 stolen from me -Node 2 (Phys 2): 628 assigned | 637 processed | 45 I stole | 36 stolen from me -Node 3 (Phys 3): 648 assigned | 665 processed | 41 I stole | 24 stolen from me +Node 0 (Phys 0): 676 assigned | 655 processed | 34 I stole | 55 stolen from me +Node 1 (Phys 1): 677 assigned | 653 processed | 28 I stole | 52 stolen from me +Node 2 (Phys 2): 606 assigned | 631 processed | 48 I stole | 23 stolen from me +Node 3 (Phys 3): 603 assigned | 623 processed | 49 I stole | 29 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 147 chunks (5.7%) +Total Cross-Socket Traffic: 159 chunks (6.2%) ================================================================= -real 0m0.440s -user 0m8.420s -sys 0m1.589s +real 0m0.451s +user 0m8.381s +sys 0m1.588s -CPU UTILIZATION: 22.747 / 28 +CPU UTILIZATION: 22.104 / 28 ----------------------------------------- @@ -7464,20 +7464,20 @@ CPU UTILIZATION: 22.747 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 686 assigned | 663 processed | 40 I stole | 63 stolen from me -Node 1 (Phys 1): 625 assigned | 634 processed | 62 I stole | 53 stolen from me -Node 2 (Phys 2): 645 assigned | 656 processed | 57 I stole | 46 stolen from me -Node 3 (Phys 3): 606 assigned | 609 processed | 59 I stole | 56 stolen from me +Node 0 (Phys 0): 656 assigned | 673 processed | 64 I stole | 47 stolen from me +Node 1 (Phys 1): 631 assigned | 655 processed | 68 I stole | 44 stolen from me +Node 2 (Phys 2): 651 assigned | 628 processed | 41 I stole | 64 stolen from me +Node 3 (Phys 3): 624 assigned | 606 processed | 50 I stole | 68 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 218 chunks (8.5%) +Total Cross-Socket Traffic: 223 chunks (8.7%) ================================================================= 2168851 real 0m0.444s -user 0m8.395s -sys 0m1.618s +user 0m8.384s +sys 0m1.634s -CPU UTILIZATION: 22.551 / 28 +CPU UTILIZATION: 22.563 / 28 ----------------------------------------- @@ -7487,18 +7487,18 @@ CPU UTILIZATION: 22.551 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.395s -user 0m7.187s -sys 0m0.531s +real 0m0.389s +user 0m7.198s +sys 0m0.532s -CPU UTILIZATION: 19.539 / 28 +CPU UTILIZATION: 19.871 / 28 ----------------------------------------- @@ -7516,11 +7516,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.419s -user 0m7.288s -sys 0m0.503s +real 0m0.394s +user 0m7.192s +sys 0m0.511s -CPU UTILIZATION: 18.594 / 28 +CPU UTILIZATION: 19.550 / 28 ----------------------------------------- @@ -7529,19 +7529,19 @@ CPU UTILIZATION: 18.594 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 684 assigned | 646 processed | 52 I stole | 90 stolen from me -Node 1 (Phys 1): 633 assigned | 638 processed | 71 I stole | 66 stolen from me -Node 2 (Phys 2): 583 assigned | 630 processed | 94 I stole | 47 stolen from me -Node 3 (Phys 3): 662 assigned | 648 processed | 54 I stole | 68 stolen from me +Node 0 (Phys 0): 639 assigned | 661 processed | 105 I stole | 83 stolen from me +Node 1 (Phys 1): 641 assigned | 648 processed | 84 I stole | 77 stolen from me +Node 2 (Phys 2): 666 assigned | 646 processed | 80 I stole | 100 stolen from me +Node 3 (Phys 3): 616 assigned | 607 processed | 82 I stole | 91 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 271 chunks (10.6%) +Total Cross-Socket Traffic: 351 chunks (13.7%) ================================================================= -real 0m0.349s -user 0m7.031s -sys 0m0.408s +real 0m0.365s +user 0m6.822s +sys 0m0.419s -CPU UTILIZATION: 21.315 / 28 +CPU UTILIZATION: 19.838 / 28 ----------------------------------------- @@ -7550,20 +7550,20 @@ CPU UTILIZATION: 21.315 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 643 processed | 61 I stole | 67 stolen from me -Node 1 (Phys 1): 612 assigned | 615 processed | 76 I stole | 73 stolen from me -Node 2 (Phys 2): 665 assigned | 646 processed | 51 I stole | 70 stolen from me -Node 3 (Phys 3): 636 assigned | 658 processed | 81 I stole | 59 stolen from me +Node 0 (Phys 0): 648 assigned | 631 processed | 63 I stole | 80 stolen from me +Node 1 (Phys 1): 617 assigned | 637 processed | 89 I stole | 69 stolen from me +Node 2 (Phys 2): 642 assigned | 634 processed | 65 I stole | 73 stolen from me +Node 3 (Phys 3): 655 assigned | 660 processed | 56 I stole | 51 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 269 chunks (10.5%) +Total Cross-Socket Traffic: 273 chunks (10.7%) ================================================================= 0 -real 0m0.348s -user 0m6.903s -sys 0m0.397s +real 0m0.349s +user 0m6.948s +sys 0m0.408s -CPU UTILIZATION: 20.977 / 28 +CPU UTILIZATION: 21.077 / 28 ----------------------------------------- @@ -7573,18 +7573,18 @@ CPU UTILIZATION: 20.977 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 21 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 19 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.399s -user 0m7.625s -sys 0m0.589s +real 0m0.420s +user 0m7.551s +sys 0m0.624s -CPU UTILIZATION: 20.586 / 28 +CPU UTILIZATION: 19.464 / 28 ----------------------------------------- @@ -7594,19 +7594,19 @@ CPU UTILIZATION: 20.586 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -1479 -real 0m0.409s -user 0m7.668s -sys 0m0.653s +1478 +real 0m0.420s +user 0m7.634s +sys 0m0.659s -CPU UTILIZATION: 20.344 / 28 +CPU UTILIZATION: 19.745 / 28 ----------------------------------------- @@ -7615,19 +7615,19 @@ CPU UTILIZATION: 20.344 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 640 assigned | 624 processed | 47 I stole | 63 stolen from me -Node 1 (Phys 1): 672 assigned | 664 processed | 47 I stole | 55 stolen from me -Node 2 (Phys 2): 629 assigned | 644 processed | 60 I stole | 45 stolen from me -Node 3 (Phys 3): 621 assigned | 630 processed | 50 I stole | 41 stolen from me +Node 0 (Phys 0): 658 assigned | 659 processed | 79 I stole | 78 stolen from me +Node 1 (Phys 1): 665 assigned | 678 processed | 67 I stole | 54 stolen from me +Node 2 (Phys 2): 616 assigned | 619 processed | 70 I stole | 67 stolen from me +Node 3 (Phys 3): 623 assigned | 606 processed | 50 I stole | 67 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 204 chunks (8.0%) +Total Cross-Socket Traffic: 266 chunks (10.4%) ================================================================= -real 0m0.366s -user 0m7.372s -sys 0m0.557s +real 0m0.376s +user 0m7.422s +sys 0m0.510s -CPU UTILIZATION: 21.663 / 28 +CPU UTILIZATION: 21.095 / 28 ----------------------------------------- @@ -7636,20 +7636,20 @@ CPU UTILIZATION: 21.663 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 718 assigned | 703 processed | 87 I stole | 102 stolen from me -Node 1 (Phys 1): 639 assigned | 641 processed | 70 I stole | 68 stolen from me -Node 2 (Phys 2): 593 assigned | 586 processed | 74 I stole | 81 stolen from me -Node 3 (Phys 3): 612 assigned | 632 processed | 100 I stole | 80 stolen from me +Node 0 (Phys 0): 635 assigned | 651 processed | 94 I stole | 78 stolen from me +Node 1 (Phys 1): 630 assigned | 625 processed | 69 I stole | 74 stolen from me +Node 2 (Phys 2): 665 assigned | 649 processed | 52 I stole | 68 stolen from me +Node 3 (Phys 3): 632 assigned | 637 processed | 79 I stole | 74 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 331 chunks (12.9%) +Total Cross-Socket Traffic: 294 chunks (11.5%) ================================================================= -3459 -real 0m0.368s -user 0m7.349s -sys 0m0.590s +3458 +real 0m0.369s +user 0m7.412s +sys 0m0.594s -CPU UTILIZATION: 21.573 / 28 +CPU UTILIZATION: 21.696 / 28 ----------------------------------------- @@ -7666,11 +7666,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.493s -user 0m8.500s -sys 0m1.664s +real 0m0.489s +user 0m8.475s +sys 0m1.648s -CPU UTILIZATION: 20.616 / 28 +CPU UTILIZATION: 20.701 / 28 ----------------------------------------- @@ -7680,19 +7680,19 @@ CPU UTILIZATION: 20.616 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 22 processed | 1 I stole | 0 stolen from me Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 18 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 2168851 -real 0m0.511s -user 0m8.554s -sys 0m1.657s +real 0m0.493s +user 0m8.428s +sys 0m1.697s -CPU UTILIZATION: 19.982 / 28 +CPU UTILIZATION: 20.537 / 28 ----------------------------------------- @@ -7701,19 +7701,19 @@ CPU UTILIZATION: 19.982 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 644 assigned | 668 processed | 65 I stole | 41 stolen from me -Node 1 (Phys 1): 614 assigned | 615 processed | 59 I stole | 58 stolen from me -Node 2 (Phys 2): 665 assigned | 646 processed | 36 I stole | 55 stolen from me -Node 3 (Phys 3): 639 assigned | 633 processed | 50 I stole | 56 stolen from me +Node 0 (Phys 0): 675 assigned | 680 processed | 52 I stole | 47 stolen from me +Node 1 (Phys 1): 666 assigned | 661 processed | 39 I stole | 44 stolen from me +Node 2 (Phys 2): 606 assigned | 613 processed | 51 I stole | 44 stolen from me +Node 3 (Phys 3): 615 assigned | 608 processed | 26 I stole | 33 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 210 chunks (8.2%) +Total Cross-Socket Traffic: 168 chunks (6.6%) ================================================================= -real 0m0.447s -user 0m8.392s -sys 0m1.600s +real 0m0.448s +user 0m8.320s +sys 0m1.615s -CPU UTILIZATION: 22.353 / 28 +CPU UTILIZATION: 22.176 / 28 ----------------------------------------- @@ -7722,20 +7722,20 @@ CPU UTILIZATION: 22.353 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 677 assigned | 665 processed | 44 I stole | 56 stolen from me -Node 1 (Phys 1): 619 assigned | 601 processed | 45 I stole | 63 stolen from me -Node 2 (Phys 2): 617 assigned | 640 processed | 58 I stole | 35 stolen from me -Node 3 (Phys 3): 649 assigned | 656 processed | 54 I stole | 47 stolen from me +Node 0 (Phys 0): 647 assigned | 663 processed | 49 I stole | 33 stolen from me +Node 1 (Phys 1): 633 assigned | 625 processed | 45 I stole | 53 stolen from me +Node 2 (Phys 2): 654 assigned | 651 processed | 39 I stole | 42 stolen from me +Node 3 (Phys 3): 628 assigned | 623 processed | 38 I stole | 43 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 201 chunks (7.8%) +Total Cross-Socket Traffic: 171 chunks (6.7%) ================================================================= 2168851 -real 0m0.440s -user 0m8.372s -sys 0m1.613s +real 0m0.446s +user 0m8.304s +sys 0m1.636s -CPU UTILIZATION: 22.693 / 28 +CPU UTILIZATION: 22.286 / 28 ----------------------------------------- @@ -7745,18 +7745,18 @@ CPU UTILIZATION: 22.693 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.140s -user 0m0.156s -sys 0m0.284s +real 0m0.143s +user 0m0.191s +sys 0m0.322s -CPU UTILIZATION: 3.142 / 28 +CPU UTILIZATION: 3.587 / 28 ----------------------------------------- @@ -7774,11 +7774,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.143s -user 0m0.175s -sys 0m0.280s +real 0m0.137s +user 0m0.180s +sys 0m0.281s -CPU UTILIZATION: 3.181 / 28 +CPU UTILIZATION: 3.364 / 28 ----------------------------------------- @@ -7787,19 +7787,19 @@ CPU UTILIZATION: 3.181 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 661 assigned | 660 processed | 0 I stole | 1 stolen from me -Node 1 (Phys 1): 607 assigned | 605 processed | 0 I stole | 2 stolen from me -Node 2 (Phys 2): 655 assigned | 660 processed | 5 I stole | 0 stolen from me -Node 3 (Phys 3): 639 assigned | 637 processed | 0 I stole | 2 stolen from me +Node 0 (Phys 0): 654 assigned | 652 processed | 2 I stole | 4 stolen from me +Node 1 (Phys 1): 665 assigned | 677 processed | 12 I stole | 0 stolen from me +Node 2 (Phys 2): 640 assigned | 633 processed | 0 I stole | 7 stolen from me +Node 3 (Phys 3): 603 assigned | 600 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 5 chunks (0.2%) +Total Cross-Socket Traffic: 14 chunks (0.5%) ================================================================= -real 0m0.169s -user 0m0.502s -sys 0m0.581s +real 0m0.165s +user 0m0.497s +sys 0m0.558s -CPU UTILIZATION: 6.408 / 28 +CPU UTILIZATION: 6.393 / 28 ----------------------------------------- @@ -7808,20 +7808,20 @@ CPU UTILIZATION: 6.408 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 669 assigned | 677 processed | 8 I stole | 0 stolen from me -Node 1 (Phys 1): 643 assigned | 638 processed | 0 I stole | 5 stolen from me -Node 2 (Phys 2): 646 assigned | 647 processed | 2 I stole | 1 stolen from me -Node 3 (Phys 3): 604 assigned | 600 processed | 0 I stole | 4 stolen from me +Node 0 (Phys 0): 660 assigned | 669 processed | 9 I stole | 0 stolen from me +Node 1 (Phys 1): 635 assigned | 631 processed | 0 I stole | 4 stolen from me +Node 2 (Phys 2): 657 assigned | 655 processed | 0 I stole | 2 stolen from me +Node 3 (Phys 3): 610 assigned | 607 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 10 chunks (0.4%) +Total Cross-Socket Traffic: 9 chunks (0.4%) ================================================================= 0 real 0m0.165s -user 0m0.475s -sys 0m0.573s +user 0m0.471s +sys 0m0.595s -CPU UTILIZATION: 6.351 / 28 +CPU UTILIZATION: 6.460 / 28 ----------------------------------------- @@ -7830,19 +7830,19 @@ CPU UTILIZATION: 6.351 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.152s -user 0m0.691s -sys 0m0.868s +real 0m0.159s +user 0m0.712s +sys 0m0.912s -CPU UTILIZATION: 10.256 / 28 +CPU UTILIZATION: 10.213 / 28 ----------------------------------------- @@ -7851,20 +7851,20 @@ CPU UTILIZATION: 10.256 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 19 assigned | 19 processed | 1 I stole | 1 stolen from me +Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (2.4%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m0.177s -user 0m0.696s -sys 0m0.991s +real 0m0.181s +user 0m0.729s +sys 0m0.977s -CPU UTILIZATION: 9.531 / 28 +CPU UTILIZATION: 9.425 / 28 ----------------------------------------- @@ -7873,19 +7873,19 @@ CPU UTILIZATION: 9.531 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 658 assigned | 660 processed | 3 I stole | 1 stolen from me -Node 1 (Phys 1): 640 assigned | 643 processed | 3 I stole | 0 stolen from me -Node 2 (Phys 2): 630 assigned | 626 processed | 0 I stole | 4 stolen from me -Node 3 (Phys 3): 634 assigned | 633 processed | 3 I stole | 4 stolen from me +Node 0 (Phys 0): 654 assigned | 655 processed | 7 I stole | 6 stolen from me +Node 1 (Phys 1): 646 assigned | 653 processed | 8 I stole | 1 stolen from me +Node 2 (Phys 2): 630 assigned | 624 processed | 1 I stole | 7 stolen from me +Node 3 (Phys 3): 632 assigned | 630 processed | 3 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.4%) +Total Cross-Socket Traffic: 19 chunks (0.7%) ================================================================= -real 0m0.221s -user 0m1.559s -sys 0m1.594s +real 0m0.223s +user 0m1.620s +sys 0m1.524s -CPU UTILIZATION: 14.266 / 28 +CPU UTILIZATION: 14.098 / 28 ----------------------------------------- @@ -7894,20 +7894,20 @@ CPU UTILIZATION: 14.266 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 661 assigned | 659 processed | 3 I stole | 5 stolen from me -Node 1 (Phys 1): 633 assigned | 638 processed | 6 I stole | 1 stolen from me -Node 2 (Phys 2): 650 assigned | 655 processed | 5 I stole | 0 stolen from me -Node 3 (Phys 3): 618 assigned | 610 processed | 0 I stole | 8 stolen from me +Node 0 (Phys 0): 638 assigned | 642 processed | 7 I stole | 3 stolen from me +Node 1 (Phys 1): 629 assigned | 624 processed | 1 I stole | 6 stolen from me +Node 2 (Phys 2): 652 assigned | 654 processed | 4 I stole | 2 stolen from me +Node 3 (Phys 3): 643 assigned | 642 processed | 1 I stole | 2 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 14 chunks (0.5%) +Total Cross-Socket Traffic: 13 chunks (0.5%) ================================================================= 2113621 -real 0m0.224s -user 0m1.587s -sys 0m1.653s +real 0m0.225s +user 0m1.584s +sys 0m1.691s -CPU UTILIZATION: 14.464 / 28 +CPU UTILIZATION: 14.555 / 28 ----------------------------------------- @@ -7916,19 +7916,19 @@ CPU UTILIZATION: 14.464 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 23 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 19 assigned | 18 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.156s -user 0m0.721s -sys 0m0.855s +real 0m0.157s +user 0m0.700s +sys 0m0.866s -CPU UTILIZATION: 10.102 / 28 +CPU UTILIZATION: 9.974 / 28 ----------------------------------------- @@ -7937,20 +7937,20 @@ CPU UTILIZATION: 10.102 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 23 assigned | 24 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 23 processed | 1 I stole | 0 stolen from me Node 1 (Phys 1): 22 assigned | 22 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 19 assigned | 19 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 18 assigned | 17 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 20 assigned | 19 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 18 assigned | 18 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= 2113621 -real 0m0.175s -user 0m0.697s -sys 0m0.907s +real 0m0.177s +user 0m0.696s +sys 0m0.926s -CPU UTILIZATION: 9.165 / 28 +CPU UTILIZATION: 9.163 / 28 ----------------------------------------- @@ -7959,19 +7959,19 @@ CPU UTILIZATION: 9.165 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 658 assigned | 662 processed | 6 I stole | 2 stolen from me -Node 1 (Phys 1): 631 assigned | 631 processed | 2 I stole | 2 stolen from me -Node 2 (Phys 2): 653 assigned | 656 processed | 3 I stole | 0 stolen from me -Node 3 (Phys 3): 620 assigned | 613 processed | 1 I stole | 8 stolen from me +Node 0 (Phys 0): 644 assigned | 649 processed | 5 I stole | 0 stolen from me +Node 1 (Phys 1): 660 assigned | 659 processed | 2 I stole | 3 stolen from me +Node 2 (Phys 2): 644 assigned | 649 processed | 6 I stole | 1 stolen from me +Node 3 (Phys 3): 614 assigned | 605 processed | 0 I stole | 9 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 12 chunks (0.5%) +Total Cross-Socket Traffic: 13 chunks (0.5%) ================================================================= -real 0m0.229s -user 0m1.576s -sys 0m1.464s +real 0m0.228s +user 0m1.529s +sys 0m1.533s -CPU UTILIZATION: 13.275 / 28 +CPU UTILIZATION: 13.429 / 28 ----------------------------------------- @@ -7980,20 +7980,20 @@ CPU UTILIZATION: 13.275 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 663 assigned | 670 processed | 9 I stole | 2 stolen from me -Node 1 (Phys 1): 649 assigned | 656 processed | 7 I stole | 0 stolen from me -Node 2 (Phys 2): 623 assigned | 612 processed | 1 I stole | 12 stolen from me -Node 3 (Phys 3): 627 assigned | 624 processed | 2 I stole | 5 stolen from me +Node 0 (Phys 0): 662 assigned | 665 processed | 6 I stole | 3 stolen from me +Node 1 (Phys 1): 650 assigned | 647 processed | 2 I stole | 5 stolen from me +Node 2 (Phys 2): 618 assigned | 616 processed | 1 I stole | 3 stolen from me +Node 3 (Phys 3): 632 assigned | 634 processed | 5 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 19 chunks (0.7%) +Total Cross-Socket Traffic: 14 chunks (0.5%) ================================================================= 2113621 -real 0m0.225s -user 0m1.589s -sys 0m1.536s +real 0m0.227s +user 0m1.556s +sys 0m1.621s -CPU UTILIZATION: 13.888 / 28 +CPU UTILIZATION: 13.995 / 28 ----------------------------------------- @@ -8003,18 +8003,18 @@ CPU UTILIZATION: 13.888 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 20 assigned | 21 processed | 1 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 0 chunks (0.0%) +Total Cross-Socket Traffic: 1 chunks (1.2%) ================================================================= -real 0m0.135s -user 0m0.052s -sys 0m0.200s +real 0m0.138s +user 0m0.058s +sys 0m0.192s -CPU UTILIZATION: 1.866 / 28 +CPU UTILIZATION: 1.811 / 28 ----------------------------------------- @@ -8024,19 +8024,19 @@ CPU UTILIZATION: 1.866 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 20 assigned | 21 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.144s -user 0m0.064s -sys 0m0.192s +real 0m0.147s +user 0m0.068s +sys 0m0.193s -CPU UTILIZATION: 1.777 / 28 +CPU UTILIZATION: 1.775 / 28 ----------------------------------------- @@ -8045,19 +8045,19 @@ CPU UTILIZATION: 1.777 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 654 assigned | 676 processed | 24 I stole | 2 stolen from me -Node 1 (Phys 1): 643 assigned | 632 processed | 2 I stole | 13 stolen from me -Node 2 (Phys 2): 636 assigned | 629 processed | 1 I stole | 8 stolen from me -Node 3 (Phys 3): 629 assigned | 625 processed | 2 I stole | 6 stolen from me +Node 0 (Phys 0): 644 assigned | 649 processed | 7 I stole | 2 stolen from me +Node 1 (Phys 1): 642 assigned | 644 processed | 4 I stole | 2 stolen from me +Node 2 (Phys 2): 639 assigned | 635 processed | 1 I stole | 5 stolen from me +Node 3 (Phys 3): 637 assigned | 634 processed | 1 I stole | 4 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 29 chunks (1.1%) +Total Cross-Socket Traffic: 13 chunks (0.5%) ================================================================= -real 0m0.157s -user 0m0.349s -sys 0m0.363s +real 0m0.155s +user 0m0.345s +sys 0m0.376s -CPU UTILIZATION: 4.535 / 28 +CPU UTILIZATION: 4.651 / 28 ----------------------------------------- @@ -8066,20 +8066,20 @@ CPU UTILIZATION: 4.535 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 643 assigned | 654 processed | 11 I stole | 0 stolen from me -Node 1 (Phys 1): 639 assigned | 638 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 641 assigned | 634 processed | 0 I stole | 7 stolen from me -Node 3 (Phys 3): 639 assigned | 636 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 643 assigned | 659 processed | 16 I stole | 0 stolen from me +Node 1 (Phys 1): 641 assigned | 635 processed | 1 I stole | 7 stolen from me +Node 2 (Phys 2): 640 assigned | 635 processed | 1 I stole | 6 stolen from me +Node 3 (Phys 3): 638 assigned | 633 processed | 0 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 12 chunks (0.5%) +Total Cross-Socket Traffic: 18 chunks (0.7%) ================================================================= 0 -real 0m0.152s -user 0m0.346s -sys 0m0.375s +real 0m0.157s +user 0m0.364s +sys 0m0.363s -CPU UTILIZATION: 4.743 / 28 +CPU UTILIZATION: 4.630 / 28 ----------------------------------------- @@ -8096,11 +8096,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.135s -user 0m0.146s -sys 0m0.333s +real 0m0.141s +user 0m0.139s +sys 0m0.325s -CPU UTILIZATION: 3.548 / 28 +CPU UTILIZATION: 3.290 / 28 ----------------------------------------- @@ -8109,20 +8109,20 @@ CPU UTILIZATION: 3.548 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 22 processed | 1 I stole | 0 stolen from me -Node 1 (Phys 1): 21 assigned | 20 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (1.2%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m0.143s -user 0m0.159s -sys 0m0.403s +real 0m0.145s +user 0m0.157s +sys 0m0.388s -CPU UTILIZATION: 3.930 / 28 +CPU UTILIZATION: 3.758 / 28 ----------------------------------------- @@ -8131,19 +8131,19 @@ CPU UTILIZATION: 3.930 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 632 assigned | 635 processed | 4 I stole | 1 stolen from me -Node 1 (Phys 1): 643 assigned | 645 processed | 4 I stole | 2 stolen from me -Node 2 (Phys 2): 645 assigned | 643 processed | 0 I stole | 2 stolen from me -Node 3 (Phys 3): 642 assigned | 639 processed | 0 I stole | 3 stolen from me +Node 0 (Phys 0): 638 assigned | 639 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 645 assigned | 644 processed | 0 I stole | 1 stolen from me +Node 2 (Phys 2): 640 assigned | 641 processed | 1 I stole | 0 stolen from me +Node 3 (Phys 3): 639 assigned | 638 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 8 chunks (0.3%) +Total Cross-Socket Traffic: 2 chunks (0.1%) ================================================================= -real 0m0.203s -user 0m0.924s -sys 0m0.901s +real 0m0.202s +user 0m0.939s +sys 0m0.905s -CPU UTILIZATION: 8.990 / 28 +CPU UTILIZATION: 9.128 / 28 ----------------------------------------- @@ -8152,20 +8152,20 @@ CPU UTILIZATION: 8.990 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 648 assigned | 649 processed | 4 I stole | 3 stolen from me -Node 1 (Phys 1): 642 assigned | 643 processed | 4 I stole | 3 stolen from me -Node 2 (Phys 2): 637 assigned | 636 processed | 2 I stole | 3 stolen from me -Node 3 (Phys 3): 635 assigned | 634 processed | 1 I stole | 2 stolen from me +Node 0 (Phys 0): 632 assigned | 638 processed | 9 I stole | 3 stolen from me +Node 1 (Phys 1): 646 assigned | 644 processed | 4 I stole | 6 stolen from me +Node 2 (Phys 2): 648 assigned | 645 processed | 3 I stole | 6 stolen from me +Node 3 (Phys 3): 636 assigned | 635 processed | 4 I stole | 5 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 11 chunks (0.4%) +Total Cross-Socket Traffic: 20 chunks (0.8%) ================================================================= 2113621 -real 0m0.202s -user 0m0.928s -sys 0m0.969s +real 0m0.203s +user 0m0.959s +sys 0m0.954s -CPU UTILIZATION: 9.391 / 28 +CPU UTILIZATION: 9.423 / 28 ----------------------------------------- @@ -8182,11 +8182,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.135s -user 0m0.158s -sys 0m0.292s +real 0m0.139s +user 0m0.141s +sys 0m0.314s -CPU UTILIZATION: 3.333 / 28 +CPU UTILIZATION: 3.273 / 28 ----------------------------------------- @@ -8204,11 +8204,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m0.137s -user 0m0.144s -sys 0m0.360s +real 0m0.142s +user 0m0.140s +sys 0m0.384s -CPU UTILIZATION: 3.678 / 28 +CPU UTILIZATION: 3.690 / 28 ----------------------------------------- @@ -8217,19 +8217,19 @@ CPU UTILIZATION: 3.678 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 652 assigned | 652 processed | 4 I stole | 4 stolen from me -Node 1 (Phys 1): 644 assigned | 647 processed | 5 I stole | 2 stolen from me -Node 2 (Phys 2): 638 assigned | 634 processed | 1 I stole | 5 stolen from me -Node 3 (Phys 3): 628 assigned | 629 processed | 3 I stole | 2 stolen from me +Node 0 (Phys 0): 648 assigned | 649 processed | 2 I stole | 1 stolen from me +Node 1 (Phys 1): 643 assigned | 642 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 630 assigned | 633 processed | 3 I stole | 0 stolen from me +Node 3 (Phys 3): 641 assigned | 638 processed | 0 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 13 chunks (0.5%) +Total Cross-Socket Traffic: 6 chunks (0.2%) ================================================================= -real 0m0.192s -user 0m0.910s -sys 0m0.851s +real 0m0.197s +user 0m0.927s +sys 0m0.856s -CPU UTILIZATION: 9.171 / 28 +CPU UTILIZATION: 9.050 / 28 ----------------------------------------- @@ -8238,20 +8238,20 @@ CPU UTILIZATION: 9.171 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 649 assigned | 650 processed | 3 I stole | 2 stolen from me -Node 1 (Phys 1): 641 assigned | 640 processed | 2 I stole | 3 stolen from me -Node 2 (Phys 2): 635 assigned | 635 processed | 2 I stole | 2 stolen from me -Node 3 (Phys 3): 637 assigned | 637 processed | 2 I stole | 2 stolen from me +Node 0 (Phys 0): 643 assigned | 645 processed | 5 I stole | 3 stolen from me +Node 1 (Phys 1): 644 assigned | 645 processed | 2 I stole | 1 stolen from me +Node 2 (Phys 2): 636 assigned | 635 processed | 2 I stole | 3 stolen from me +Node 3 (Phys 3): 639 assigned | 637 processed | 1 I stole | 3 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 9 chunks (0.4%) +Total Cross-Socket Traffic: 10 chunks (0.4%) ================================================================= 2113621 -real 0m0.193s -user 0m0.939s -sys 0m0.903s +real 0m0.200s +user 0m0.952s +sys 0m0.909s -CPU UTILIZATION: 9.544 / 28 +CPU UTILIZATION: 9.305 / 28 ----------------------------------------- @@ -8260,19 +8260,19 @@ CPU UTILIZATION: 9.544 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 0 (Phys 0): 22 assigned | 22 processed | 0 I stole | 0 stolen from me Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 19 assigned | 19 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m0.218s -user 0m2.775s -sys 0m1.125s +real 0m0.222s +user 0m2.776s +sys 0m1.078s -CPU UTILIZATION: 17.889 / 28 +CPU UTILIZATION: 17.360 / 28 ----------------------------------------- @@ -8290,11 +8290,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 0 -real 0m0.219s -user 0m2.782s -sys 0m1.128s +real 0m0.226s +user 0m2.784s +sys 0m1.079s -CPU UTILIZATION: 17.853 / 28 +CPU UTILIZATION: 17.092 / 28 ----------------------------------------- @@ -8303,19 +8303,19 @@ CPU UTILIZATION: 17.853 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 687 assigned | 687 processed | 28 I stole | 28 stolen from me -Node 1 (Phys 1): 642 assigned | 625 processed | 20 I stole | 37 stolen from me -Node 2 (Phys 2): 610 assigned | 629 processed | 36 I stole | 17 stolen from me -Node 3 (Phys 3): 623 assigned | 621 processed | 24 I stole | 26 stolen from me +Node 0 (Phys 0): 643 assigned | 627 processed | 29 I stole | 45 stolen from me +Node 1 (Phys 1): 677 assigned | 697 processed | 59 I stole | 39 stolen from me +Node 2 (Phys 2): 629 assigned | 622 processed | 27 I stole | 34 stolen from me +Node 3 (Phys 3): 613 assigned | 616 processed | 28 I stole | 25 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 108 chunks (4.2%) +Total Cross-Socket Traffic: 143 chunks (5.6%) ================================================================= -real 0m0.247s -user 0m2.742s -sys 0m1.378s +real 0m0.253s +user 0m2.835s +sys 0m1.388s -CPU UTILIZATION: 16.680 / 28 +CPU UTILIZATION: 16.691 / 28 ----------------------------------------- @@ -8324,20 +8324,20 @@ CPU UTILIZATION: 16.680 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 641 assigned | 647 processed | 42 I stole | 36 stolen from me -Node 1 (Phys 1): 628 assigned | 613 processed | 31 I stole | 46 stolen from me -Node 2 (Phys 2): 655 assigned | 662 processed | 42 I stole | 35 stolen from me -Node 3 (Phys 3): 638 assigned | 640 processed | 34 I stole | 32 stolen from me +Node 0 (Phys 0): 629 assigned | 613 processed | 32 I stole | 48 stolen from me +Node 1 (Phys 1): 644 assigned | 659 processed | 47 I stole | 32 stolen from me +Node 2 (Phys 2): 627 assigned | 634 processed | 39 I stole | 32 stolen from me +Node 3 (Phys 3): 662 assigned | 656 processed | 34 I stole | 40 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 149 chunks (5.8%) +Total Cross-Socket Traffic: 152 chunks (5.9%) ================================================================= 0 -real 0m0.259s -user 0m2.775s -sys 0m1.459s +real 0m0.250s +user 0m2.865s +sys 0m1.331s -CPU UTILIZATION: 16.347 / 28 +CPU UTILIZATION: 16.784 / 28 ----------------------------------------- @@ -8347,18 +8347,18 @@ CPU UTILIZATION: 16.347 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 21 assigned | 21 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 20 assigned | 20 processed | 0 I stole | 0 stolen from me -Node 2 (Phys 2): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 21 assigned | 21 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.166s -user 0m14.618s -sys 0m11.714s +real 0m1.177s +user 0m14.678s +sys 0m11.938s -CPU UTILIZATION: 22.583 / 28 +CPU UTILIZATION: 22.613 / 28 ----------------------------------------- @@ -8376,11 +8376,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m1.153s -user 0m14.698s -sys 0m11.980s +real 0m1.165s +user 0m14.632s +sys 0m12.191s -CPU UTILIZATION: 23.137 / 28 +CPU UTILIZATION: 23.024 / 28 ----------------------------------------- @@ -8390,18 +8390,18 @@ CPU UTILIZATION: 23.137 / 28 NUMA TELEMETRY (CHUNKS) ================================================================= Node 0 (Phys 0): 643 assigned | 643 processed | 1 I stole | 1 stolen from me -Node 1 (Phys 1): 644 assigned | 643 processed | 0 I stole | 1 stolen from me -Node 2 (Phys 2): 636 assigned | 636 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 639 assigned | 640 processed | 1 I stole | 0 stolen from me +Node 1 (Phys 1): 642 assigned | 641 processed | 1 I stole | 2 stolen from me +Node 2 (Phys 2): 640 assigned | 641 processed | 2 I stole | 1 stolen from me +Node 3 (Phys 3): 637 assigned | 637 processed | 1 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 2 chunks (0.1%) +Total Cross-Socket Traffic: 5 chunks (0.2%) ================================================================= real 0m1.156s -user 0m14.541s -sys 0m12.103s +user 0m14.674s +sys 0m12.218s -CPU UTILIZATION: 23.048 / 28 +CPU UTILIZATION: 23.262 / 28 ----------------------------------------- @@ -8410,20 +8410,20 @@ CPU UTILIZATION: 23.048 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 640 assigned | 640 processed | 0 I stole | 0 stolen from me -Node 1 (Phys 1): 644 assigned | 645 processed | 1 I stole | 0 stolen from me -Node 2 (Phys 2): 640 assigned | 640 processed | 0 I stole | 0 stolen from me -Node 3 (Phys 3): 638 assigned | 637 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 644 assigned | 644 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 639 assigned | 639 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 639 assigned | 639 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 640 assigned | 640 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 1 chunks (0.0%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m1.158s -user 0m14.730s -sys 0m12.207s +real 0m1.171s +user 0m14.701s +sys 0m12.480s -CPU UTILIZATION: 23.261 / 28 +CPU UTILIZATION: 23.211 / 28 ----------------------------------------- @@ -8440,11 +8440,11 @@ Node 3 (Phys 3): 20 assigned | 20 processed | 0 I stole | 0 stolen from me Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.130s -user 0m14.526s -sys 0m11.591s +real 0m1.145s +user 0m14.541s +sys 0m11.772s -CPU UTILIZATION: 23.112 / 28 +CPU UTILIZATION: 22.980 / 28 ----------------------------------------- @@ -8462,11 +8462,11 @@ Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= 2113621 -real 0m1.140s -user 0m14.576s -sys 0m11.735s +real 0m1.153s +user 0m14.676s +sys 0m11.818s -CPU UTILIZATION: 23.079 / 28 +CPU UTILIZATION: 22.978 / 28 ----------------------------------------- @@ -8475,19 +8475,19 @@ CPU UTILIZATION: 23.079 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 638 assigned | 640 processed | 2 I stole | 0 stolen from me -Node 1 (Phys 1): 642 assigned | 642 processed | 1 I stole | 1 stolen from me -Node 2 (Phys 2): 642 assigned | 641 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 640 assigned | 639 processed | 0 I stole | 1 stolen from me +Node 0 (Phys 0): 644 assigned | 644 processed | 0 I stole | 0 stolen from me +Node 1 (Phys 1): 641 assigned | 641 processed | 0 I stole | 0 stolen from me +Node 2 (Phys 2): 641 assigned | 641 processed | 0 I stole | 0 stolen from me +Node 3 (Phys 3): 636 assigned | 636 processed | 0 I stole | 0 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 3 chunks (0.1%) +Total Cross-Socket Traffic: 0 chunks (0.0%) ================================================================= -real 0m1.132s -user 0m14.616s -sys 0m11.689s +real 0m1.144s +user 0m14.537s +sys 0m11.968s -CPU UTILIZATION: 23.237 / 28 +CPU UTILIZATION: 23.168 / 28 ----------------------------------------- @@ -8496,20 +8496,20 @@ CPU UTILIZATION: 23.237 / 28 ================================================================= NUMA TELEMETRY (CHUNKS) ================================================================= -Node 0 (Phys 0): 639 assigned | 640 processed | 2 I stole | 1 stolen from me -Node 1 (Phys 1): 644 assigned | 643 processed | 1 I stole | 2 stolen from me -Node 2 (Phys 2): 639 assigned | 638 processed | 0 I stole | 1 stolen from me -Node 3 (Phys 3): 640 assigned | 641 processed | 1 I stole | 0 stolen from me +Node 0 (Phys 0): 642 assigned | 644 processed | 2 I stole | 0 stolen from me +Node 1 (Phys 1): 641 assigned | 641 processed | 1 I stole | 1 stolen from me +Node 2 (Phys 2): 642 assigned | 641 processed | 0 I stole | 1 stolen from me +Node 3 (Phys 3): 637 assigned | 636 processed | 0 I stole | 1 stolen from me ----------------------------------------------------------------- -Total Cross-Socket Traffic: 4 chunks (0.2%) +Total Cross-Socket Traffic: 3 chunks (0.1%) ================================================================= 2113621 -real 0m1.136s -user 0m14.675s -sys 0m11.849s +real 0m1.154s +user 0m14.606s +sys 0m12.148s -CPU UTILIZATION: 23.348 / 28 +CPU UTILIZATION: 23.183 / 28 ----------------------------------------- @@ -8533,12 +8533,12 @@ NAME: f3 SIZE: 167808321 bytes LINE COUNT: 2113621 lines -total sys = 4334018 ms +total sys = 4367808 ms -total user = 7367140 ms +total user = 7381408 ms -total real = 480803 ms +total real = 482860 ms -OVERALL CPU UTILIZATION: 24.336 / 28 +OVERALL CPU UTILIZATION: 24.332 / 28 diff --git a/forkrun_ring.c b/forkrun_ring.c index 87ee8e5d..2b3d0c84 100644 --- a/forkrun_ring.c +++ b/forkrun_ring.c @@ -4241,16 +4241,13 @@ static int do_lockfree_claim(struct WorkerBatchState *out, bool blocking) { // (e) waits for child N, // (f) shadow-orphan-rescues N+1 if child N failed. static int ring_exec_main(int argc, char **argv) { - // Usage: ring_exec [fixed_args...] if (argc < 5) return EXECUTION_FAILURE; int fd = atoi(argv[1]); size_t length = (size_t)atoll(argv[2]); char delim = argv[3][0]; - int fixed_argc = argc - 4; - // 1. Ensure baseline capacity for fixed arguments if (tls_argv_cap < (size_t)(fixed_argc + 1024)) { tls_argv_cap = fixed_argc + 1024; char **new_argv = realloc(tls_argv, tls_argv_cap * sizeof(char *)); @@ -4258,15 +4255,11 @@ static int ring_exec_main(int argc, char **argv) { tls_argv = new_argv; } - // 2. Load fixed command and args directly from Bash's parsed argv for (int i = 0; i < fixed_argc; i++) { tls_argv[i] = argv[4 + i]; } - // 3. TOKENIZE BATCH N - // If the previous cycle's overlap already tokenized this batch, skip parsing - // entirely — the kernel copied argv into the child at spawn, so tls_argv and - // tls_map_buf still hold N+1's data from last cycle, which IS batch N now. + // 1. TOKENIZE BATCH N (If not already done by the prefetcher) if (!prefetch_tokens_ready) { size_t batch_argc = 0; int tok = do_tokenize(fd, length, tls_batch_offset, delim, NULL, fixed_argc, &batch_argc); @@ -4277,40 +4270,33 @@ static int ring_exec_main(int argc, char **argv) { prefetch_tokens_ready = false; } - // 4. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) + // 2. SHIELD AGAINST BASH'S JOB CONTROL (Block SIGCHLD) sigset_t set, oset; sigemptyset(&set); sigaddset(&set, SIGCHLD); sigprocmask(SIG_BLOCK, &set, &oset); - // 5. SPAWN CHILD N (returns immediately; child runs concurrently with prefetch below) + // 3. SPAWN CHILD N (returns immediately; child runs concurrently) pid_t pid; int ret = posix_spawnp(&pid, tls_argv[0], NULL, NULL, tls_argv, environ); - // 6. THE LATENCY HIDING OVERLAP - // Child N is now running. Use its execution time to prefetch and pre-tokenize - // Batch N+1. This is non-blocking: if the ring has no data yet (scanner is still - // ingesting), do_lockfree_claim returns 1 and we degrade gracefully to zero overhead. + // 4. THE LATENCY HIDING OVERLAP (Fetch N+1) if (ret == 0 && state && !atomic_load_relaxed(&state[0].emergency_abort)) { + // Use non-blocking mode: if the ring is empty, gracefully fall back to zero overhead if (do_lockfree_claim(&prefetched_batch, false) == 0) { have_prefetch = true; - // Pre-tokenize N+1 directly into tls_argv. Safe because posix_spawnp - // already copied argv into the child's address space — the parent's - // tls_argv is free to be overwritten. + // Pre-tokenize N+1 directly into tls_argv. + // Safe because posix_spawnp already copied argv into the child's address space. size_t next_argc = 0; if (do_tokenize(fd, prefetched_batch.length, (off_t)prefetched_batch.offset, delim, NULL, fixed_argc, &next_argc) == EXECUTION_SUCCESS) { tls_argv[fixed_argc + next_argc] = NULL; prefetch_tokens_ready = true; } - // If tokenize failed, have_prefetch stays true but prefetch_tokens_ready - // stays false. ring_exec will re-tokenize next cycle (safe fallback). } - // ret 1 = no data yet, ret 2 = EOF: have_prefetch stays false. - // ring_claim_main will do a synchronous blocking claim next iteration. } - // 7. WAIT FOR CHILD N + // 5. WAIT FOR CHILD N int status = 0; if (ret == 0) { while (waitpid(pid, &status, 0) == -1) { @@ -4318,13 +4304,9 @@ static int ring_exec_main(int argc, char **argv) { } } - // 8. Restore signal mask sigprocmask(SIG_SETMASK, &oset, NULL); - // 9. THE SHADOW ORPHAN RESCUE - // Child N failed. We already atomically claimed N+1 from the ring — if we just - // return failure, that batch is gone forever. Escrow it so the Bash retry trap - // can safely reprocess N while N+1 waits in the pipe for the next worker. + // 6. THE SHADOW ORPHAN RESCUE bool child_failed = (ret != 0) || (WIFEXITED(status) && WEXITSTATUS(status) != 0) || WIFSIGNALED(status); @@ -4335,7 +4317,7 @@ static int ring_exec_main(int argc, char **argv) { struct EscrowPacket ep = { .idx = prefetched_batch.idx, .cnt = prefetched_batch.cnt, - .num_kills = prefetched_batch.num_kills + .num_kills = 0 // Must be 0 for the orphaned batch! }; ssize_t ew; do { @@ -4351,7 +4333,6 @@ static int ring_exec_main(int argc, char **argv) { prefetch_tokens_ready = false; } - // 10. RETURN if (ret != 0) return EXECUTION_FAILURE; if (WIFEXITED(status)) return (WEXITSTATUS(status) == 0) ? EXECUTION_SUCCESS : WEXITSTATUS(status); if (WIFSIGNALED(status)) return 128 + WTERMSIG(status); diff --git a/forkrun_ring.native.so b/forkrun_ring.native.so deleted file mode 100755 index fa08a9c36985ae7bfaedee7445245ab921bc881a..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 141896 zcmbS!3t$x0_4jVb!t#g{D`pg76zeUr>n*bD zInO4W4Cm>!tCL3lw?uXGgQwpv=R8@Ke|+-4Ne5NK$3I815dNH}(_b&(SnofL&nef+ z%J{R{>AH4z(bWG*#(V#+gjeAjeN`B&PRNA&1Eub%MS0`cncs-m=1 zlOC<})^?Ja8g&F&siEKDUu{qxQiN}3zSW$<-_S#Z*{#(i@Ls~?f>kB(PQoO^S}O1- zgvl0bk-!@Xb4pm{0JsrgYb!jn*{zH;hzw$ z68JX4ClOvM@Gl8dG}a=4uOZCYXO#E_!Pp^1-^uE7U9VPUqJX&!V?8P zm+)zX^8_A3_;kV}1wM`N8H9ZT|Ag>B!kGg1A$%rbm%wR+2N7;P%JCmL9k7pZv%rT4 z4<_6s@Ls}02v-Tblki!DmkRs|VL#zT0&gTdlyJGgYYCrCI3jQj;d2O27kD}0VT30O z{7=H!geMC8D&cbp=L!5G;o*cw3j8eL5rlmLKTh~O!kGd;O8BRQT>_U9KA&*wcOrkn zBMCPPJcDo!;U5r8jtD%S@Wq6u z3w#OT(S#=pd;#GA;fVsDOZXDPc>)h1JcjT{flnhmmatFYpAgO^oGEZ0!apbM5;%?U 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